International Management Competencies Essay Example | Topics and Well Written Essays - 500 words - 1

International Management Competencies - Essay Example For this reason, embracing Internet technology to gain information about the market composition may work positively for my organisation. Through this knowledge, it is easier for me as a manager to understand the manner of reaction of all customers to diverse ideas prevailing in the market. Following globalisation of businesses, it is advisable for me as a manager to ensure that all the accounting and book keeping methods follow the international standards. Burton (2012) argues that anybody in any part of the world who may be interested in knowing about the organisations financial status may have easy time interpreting the financial implications on the records. This would create an international business climate which would come along with numerous advantages in my position as a manager according to the explanations in the subsequent sections. The article elaborates about culture and business ethics having direct relations which can be viewed in different dimensions. There are issues such as law, religion and other means of relation which define the culture of a given business community. This relates to cross-cultural ideas which bring about change in the market culture and norms. This may vary from country to country depending on the dominant values in the field of business within that country. As a manager, it is crucial for me to determine the cultures and practice of various countries so as to make sound decision in every involvement with any country. On the same note, I realize that development of better communication and diversity within a country would mean that more tolerance would be exhibited compared to pure composition in a society. Burton (2012), in his research, supports that the best way to go as a manager is to ensure that all the instruments used in cultural impact determination are non bias. In determining all the dimensions, I must consider that functional role remains constant across all countries. When I am developing a design for a

Lightweight Community-Driven Approach to Support Ontology Evolution Essay

Lightweight Community-Driven Approach to Support Ontology Evolution - Essay Example The chapter goes on to identify the advantage of ontology evolution, the lack of systematic approach for ontology evolution and explains the motivation for this study. The chapter ends with the objectives of the study and thesis structure. 1.2 Ontology Definitions The term â€Å"Ontology† is derived from its usage in philosophy where it means the study of being or existence as well as the basic categories (Witmer 2004). Therefore, it is now used to refer to what exists in a system model. Definition 1: According to the Merriam-Webster Dictionary (2011), â€Å"It is a particular nature of being or the kinds of things that have existence. Definition 2: Gruber (1993), on the other hand, provides a more concrete definition of Ontology. He defines it as a study which explicitly explains concepts and relationships (Gruber 1993). The set of concepts (e.g. classes, relations, functions) are used to represent and describe domain knowledge. For example, in oil and gas industry there is an established ontology for Statoil in Norway (Association 2008) a standard library related to an oil and gas domain. 1.3 Ontology Editor Ontology Editor is an application which is developed to view and edit ontology. In the past few years many applications have been developed such as OilEd (Bechhofer, Horrocks et al. 2001), OntoEdit (Sure, Erdmann et al. 2002), Protege (Gennari, Musen et al. 2003) and Web-Protege (Tudorache, Vendetti et al. 2008). Further details are explained below about each ontology editor: - OilEd: OilEd was developed in Manchester University. It is a simple ontology editor that provides further guidance in the development of Ontology Interchange Language (OIL)-based ontologies (Bechhofer, Horrocks et al. 2001), which is basically a web-based representation of ontologies organized to make it accessible and usable (Cover, 2000). It is the one which pioneers ontology editing (Bechhofer, Horrocks et al. 2001). - OntoEdit: OntoEdit was developed by the Knowledge Ma nagement Group at University of Karsnuhe Institute AFIB. It provides an ontology development that allows collaboration and inferencing. The method involves three main steps which start with requirements specification, refinement and evaluation. The first step is where the ontology engineers and domain experts meet and work towards identifying the goal of the ontology, description of the domain, and the availability of references. Design guidelines are also established in this step. Then, the team then makes the ontology in the refinement phase. Finally, the ontology requires evaluation according to its requirements specification by identifying possible errors in the ontology and efficiency for enabling collaborative work (Sure, Erdmann et al. 2002). - Protege: Protege was developed by Mark Musen at Stanford University. It is an ontology editor which has come a long way. Protege started in 1987 as a small application, which was aimed at building knowledge acquisition tools. Protege h as then been developed further, providing many new features for each version that has been released. Currently, there are hundreds of individuals and research groups are using Protege (Gennari, Musen et al. 2003). - Web-Protege: Web-Protege is a web version of Protege, also developed in Stanford University. This allows the users who have access to view and edit the ontology from the internet (Tudorache, Vende

Online Behaviors And Impression Management Essay Example for Free

Online Behaviors And Impression Management Essay Introduction With the rapid development of technology, the Internet has become an effective mechanism for social networking. People can not deny the fact that a successful social networking is more possible to lead a successful life. A personal impression serves as an important role in establishing new networks and managing old ones. It was proved that people have more opportunities presenting themselves in the computer-coordinated communication settings than face-to-face environments. Therefore, regardless of generations, the ways how people interact with one another have been greatly changed by online social sites. The purpose of this study is to understand how people utilize online social sites to manage their personal impression and how they behave on social media; also, people utilize social media in order to gratify their social needs such as their friendship maintenance. The thesis of this paper is that social media influences personal behaviors as well as their impression management and it also has positive impacts on people friendships performance. Personal Behavior on Social Media Individual behaviors may be restrained because of their awareness that their behaviors might possibly be seen by other people, and the fact that people tempt to look more appealing in any social occasions is obvious (Jeong, 2011). Since social media is served as a platform which is opened to public, people tend to pay more attention to how they appear and behave online. An experiment from Denton (2012) indicates that participants within heterogeneous networks such as Facebook have more desire to shift their impressions to others. A heterogeneous network is a network which is established for people without same interests, religions or common interests; in other words, people are able to speak or act freely on those websites. This experiment explains further that people manage or even shift their image based on others views and attitudes. According to Cummings (2012), the setting of profiles provides an opportunity for ones’ social life; people put effort into presenting a better image which aims at influencing others within the network. Jeong (2012) also declares that the process in which individuals attempt to control their impression with others is called â€Å"impression management†. Impression management can be used interchangeably with the term â€Å"self-presentation†, and its goal is to elevate people’s public image by performing behaviors based on how others evaluate them. Jeong also states that impression management usually occurs together with social desirability. Social desirability is defined as an individual’s tendency to describe themselves and behave in a manner in which they believe they will be viewed favorably in a situation. Moreover, Jeong also points out three main characteristics of self-presentation in online media platforms. They are asynchronous, malleable and selective. Asynchronous means that people can edit and update self-presentational cues deliberately over time. Malleable means people can simply manipulate those cues. Denton (2012) explains further by stating that people behave differently in different situations or interact with different people with whom they have specific relationships. For example, a lazy and incompetent employee may spend his evening as a passionate and assiduous worker volunteer or he behaves as a hard-working worker only under supervision; in this case, employers might misunderstand that he is truly a diligent worker. Thirdly, selective means people can improve their impression by choosing specific cues. Jeong explains this term by giving an example that individuals are more likely to donate or show their supports for charity campaigns as long as they realize that their participation would be noticeable to other people. Besides, there are some companies tend to elevate their images by sponsoring nonprofit organizations. To conclude, in general, people tend to behave favorably and try to create a positive impression to others on social media. Impression Management on Social Media Social media has been a new and easy platform for people managing their impression. Sameer (2007) states that document preparation programs make it relatively easy to manipulate the appearance of profiles; also, programmability helps people keep track of contents to the audience, and browser application provide an easy way to distribute the original or modified profiles. Therefore, Krisanic (2008) concludes from her research that impression management has been commonly carried out by those who involved in social networking activities. Jeong (2011) also states that online media platforms are expected to provide people with a greater opportunity for impression management, and because of its â€Å"public display† which enables participants to articulate and make their social networks more manifest; furthermore, Ellison (2008) declares that this kind of â€Å"public display of connection† serves as important signal that helps people navigate their networked social world. Cummings (2012) supports his idea. He points out that social network sites provide people a channel to present themselves digitally, and also gives them another way to provide details about themselves and establish or maintain their relationships in their own social network. Also, profile owners are not the only ones who are able to provide information on their own pages. Most sites such as Facebook and LinkedIn allow those who are involved in the connection to create additional information, and the use of wall posts and the recommendation are the examples (Cummings, 2012). All in all, the main characteristics of social network sites include the capability to make connection between people and share personal information; on top of that, it offers an easy way for people to manage their personal impressions. Friendships Performance on Social Media The articulation of friendship connections is another facet of impression management; it might possibly be viewed from others as an identity marker to profile owners (boyd Ellison, 2008). Although boyd and Ellison argue that online audiences’ comments may dominate user behaviors, Vallor (2012) thinks that those interactions are part of the reciprocity which serves a prime function maintaining friendships. Reciprocity is an original biological stimulus that operates as the core of human sociology and is the mutual characteristic of different types of friendships (Vallor, 2012). Take Facebook as an example, reciprocity emerge with diverse forms; it begins with the friend requests and accepting invitations correspondingly, responding to friends’ status by pressing â€Å"like† button, sharing photos and videos online, comments on friends’ status, and â€Å"tag† friends on pictures or posts. Therefore, a study from Vallor (2012) shows that instead of di minishing people’s interactions in their real lives, online social sites actually extend chances for such interaction. Vallor (2012) also declares that social media can support friendships. Many social network sites allow additional information, and which encourage people to list hobbies, post photos, and interact with other individuals within the network (Cummings, 2012). Furthermore, social network sites help individuals to manage contacts beyond traditional software like outlook, and they also help incorporate visual information such as pictures of contacts (Cummings, 2012); hence, the online social media offers a precious function of recombining efficiently with friends in the past (Vallor, 2012). To conclude, it is true that these sites help participants perceiving more sense of social value and connection; also, social network sites help reinforce participant’s desire to maintain their friendships (Vallor, 2012). Conclusion As online social networking sites as a new media technology comes out in our society, individuals have more opportunity than ever before to present themselves in public by using them. These sites allow users to make self-presentation by creating their own profile pictures, personal information, photos, videos, and their activities. Impression management is related to social networking sites use because individuals tend to develop different self-presentation depending on the audiences online. From those studies we were discussed, people tend to behave favorable to their audiences. However, the authenticity of profile information comes into concern since everything that shows on people’s profiles may dominate their images to others; whether this fact leads to negative problem of social networking sites may still need to be further investigated and researched. From another aspect, we can conclude that social networking sites have a positive impact on friendship performance. Although some studies argue that the online social networking sites may damage the traditional meaning of friendship, it serves as a valuable tool maintaining the friendship in people real lives. All in all, social network sites if manage properly; they can of course offer very concrete benefits to people social networking lives. References boyd, D. Ellison, N. (2008). Social Network Sites: Definition, History, and Scholarship. (pp. 219-220). Journal of Computer-Mediated Communication 13(2008) 210-230. Cummings, J. (2012). Virtual First Impression Matter: The effect of social networking sites on Impression formation in virtual teams. ProQuest Dissertations and Theses 2012 pg. n/a Ellison, A. S. W. (2012). Impression Formation in a Social Network Context. ProQuest Dissertations and Theses 2012 pg. n/a Jeong, H. J. (2011). The Effectiveness of Corporate Social Responsibility (CSR) Campaigns on Consumer Responses to Brand in Social Media: Impression Management Perspectives. ProQuest Dissertations and Theses 2011 pg. n/a Krisanic, K. (2008). Motivation and Impression Management: Predictors of social networking site use and users behaviors. ProQuest Dissertations and Theses 2008 pg. n/a Sameer, B. (2008). First Impression formation in electronic profiles. ProQuest Dissertations and Theses 2008 pg. n/a Vallor, S. (2011). Flo urishing on Facebook: virtue friendship new social media. Springer Science and Business Media B.V. 2011

Information Retrieval from Large Databases: Pattern Mining

Information Retrieval from Large Databases: Pattern Mining Efficient Information Retrieval from Large Databases Using Pattern Mining Kalaivani.T, Muppudathi.M Abstract With the widespread use of databases and explosive growth in their sizes are reason for the attraction of the data mining for retrieving the useful informations. Desktop has been used by tens of millions of people and we have been humbled by its usage and great user feedback. However over the past seven years we have also witnessed some changes in how users store and access their own data, with many moving to web based application. Despite the increasing amount of information available in the internet, storing files in personal computer is a common habit among internet users. The motivation is to develop a local search engine for users to have instant access to their personal information.The quality of extracted features is the key issue to text mining due to the large number of terms, phrases, and noise. Most existing text mining methods are based on term-based approaches which extract terms from a training set for describing relevant information. However, the quality of the extract ed terms in text documents may be not high because of lot of noise in text. For many years, some researchers make use of various phrases that have more semantics than single words to improve the relevance, but many experiments do not support the effective use of phrases since they have low frequency of occurrence, and include many redundant and noise phrases. In this paper, we propose a novel pattern discovery approach for text mining.To evaluate the proposed approach, we adopt the feature extraction method for Information Retrieval (IR). Keywords –Pattern mining, Text mining, Information retrieval, Closed pattern. 1.Introduction In the past decade, for retrieving an information from the large database a significant number of datamining techniques have been presented that includes association rule mining, sequential pattern mining, and closed pattern mining. These methods are used to find out the patterns in a reasonable time frame, but it is difficult to use the discovered pattern in the field of text mining. Text mining is the process of discovering interesting information in the text documents. Information retrieval provide many methods to find the accurate knowledge form the text documents. The most commonly used method for finding the knowledge is the phrase based approaches, but the method have many problems such as phrases have low frequency of occurrence, and there are large number of noisy phrases among them.If the minimum support is decreased then it will create lot of noisy pattern 2.Pattern Classification Method To find the knowledge effectively without the problem of low frequency and misinterpretation a pattern based approach(Pattern classification method) is discovered in this paper. This approach first find out the common character of pattern and evaluates the weight of the terms based on distribution of terms in the discovered pattern. It solves the problem of misinterpretation. The low frequency problem can also be reduced by using the pattern in the negatively trained examples. To discover patterns many algorithms are used such as Apriori algorithm, FP-tree algorithm, but these algorithms does not tell how to use the discovered patterns effectively. The pattern classification method uses closed sequential pattern to deal with large amount of discovered patterns efficiently. It uses the concept of closed pattern in text mining. 2.1 Preprocessing The first step towards handling and analyzing textual data formats in general is to consider the text based information available in free formatted text documents.Real world databases are highly susceptible to noisy, missing, and inconsistent data due to their huge size. These low quality data will lead to low quality mining results. Initially the preprocessing is done with text document while storing the content into desktop systems.Commonly the information would be processed manually by reading thoroughly and then human domain experts would decide whether the information was good or bad (positive or negative). This is expensive in relation to the time and effort required from the domain experts. This method includes two process. 2.1.1 Removing stop words and stem words To begin the automated text classification process the input data needs to be represented in a suitable format for the application of different textual data mining techniques, the first step is to remove the un-necessary information available in the form of stop words.Stop words are words that are deemed irrelevant even though they may appear frequently in the document. These are verbs, conjunctions, disjunctions and pronouns, etc. (e.g. is, am, the, of, an, we, our). These words need to be removed as they are less useful in interpreting the meaning of text. Stemming is defined as the process of conflating the words to their original stem, base or root. Several words are small syntactic variants of each other since they share a common word stem. In this paper simple stemming is applied where words e.g. ‘deliver’, ‘delivering’ and ‘delivered’ are stemmed to ‘deliver’. This method helps to capture whole information carrying term space and also reduces the dimensions of the data which ultimately affects the classification task. There are many algorithms used to implement the stemming method. They are Snowball, Lancaster and the Porter stemmer. Comparing with others Porter stemmer algorithm is an efficient algorithm. It is a simple rule based algorithm that replaces a word by an another. Rules are in the form of (condition)s1->s2 where s1, s2 are words. The replacement can be done in many ways such as, replacing sses by ss, ies by i, replacing past tense and progressive, cleaning up, replac ing y by i, etc. 2.1.2 Weight Calculation The weight of the each term is calculated by multiplying the term frequency and inverse document frequency. Term frequency find the occurrence of the individual terms and counts. Inverse document frequency is a measure of whether a term is common or rare across all documents. Term Frequency: Tf(t,d)=0.5+0.5*f(t,d)/max{f(w,d):wbelongs to d} Where d represents single document and t represents the terms Inverse Document Frequency: IDF(t,D)= log(Total no of doc./No of doc. Containing the term) Where D represents the total number of documents Weight: Wt=Tf*IDF 2.2 Clustering Cluster is a collection of data objects. Similar to one another within the same cluster. Cluster analysis will find similarities between data according to the characteristics found in the data and grouping similar data objects into clusters.Clustering is defined as a process of grouping data or information into groups of similar types using some physical or quantitative measures. It is an unsupervised learning. Cluster analysis used in many applications such as, pattern recognition, data analysis and web for information discovery. Cluster analysis support many types of data like, Data matrix, Interval scaled variables, Nominal variables, Binary variables and variables of mixed types. There are many methods used for clustering. The methods are partitioning methods, hierarchical methods, density based methods, grid based methods and model based methods. In this paper partitioning method is proposed for clustering. 2.2.1 Partitioning methods This method classifies the data into k-groups, which together satisfy the following requirements: (1) each group must contain at least one object, (2) each object must belong to exactly one group. Given a database of n objects, a partitioning method constructs k partitions of the data, where each partition represents a cluster and k 2.2.2 K-means algorithm K-means is one of the simplest unsupervised learning algorithms. It takes the input parameter, k, and partitions a set of n objects into k-clusters so that the resulting intra cluster similarity is high but the inter cluster similarity is low. It is centroid based technique. Cluster similarity is measured in regard to the mean value of the objects in a cluster, which can be viewed as the clusters centroid. Input:k: the number of clusters, D: a data set containing n objects. Output: A set of k clusters. Methods: Select an initial partition with k clusters containing randomly chosen samples, and compute the centroids of the clusters. Generate a new partition by assigning each sample to the closest cluster center. Compute new cluster centers as the centroids of the cluster. Repeat steps 2 and 3 until an optimum value of the criterion function is found or until the cluster membership stabilizes. This algorithm faster than hierarchical clustering. But it is not suitable to discover clusters with non-convex shapes. Fig.1. K-Means Clustering 2.3 Classification It predicts categorical class labels and classifies the data based on the training set and the values in classifying the attribute and uses it in classifying the new data. Data classification is a two step process (1) learning, (2) classification. Learning can be classified into two types supervised and unsupervised learning. The accuracy of a classifier refers to the ability of a given classifier to correctly predict the class label of new or previously unseen data. There are many classification methods are available such as, K-nearest neighbor, Genetic algorithm, Rough Set Approach, and Fuzzy Set approaches.The classification technique measures the nearing occurrence. It assumes the training set includes not only the data in the set but also the desired classification for each item. The classification is done through training samples, where the entire training set includes not only the data in the set, but also the desired classification for each item. The Proposed approaches find the minimum distance from the new or incoming instance to the training samples. On the basis of finding the minimum distance only the closest entries in the training set are considered and thenew item is placed into the classwhich contains the most items of the K. Here classify thesimilarity text documents and file indexing is performed to retrieve the file in effective manner. 3. Result and Discussion The input file is given and initial preprocessing is done with that file. To find the match with any other training sample inverse document frequency is calculated. To find the similarities between documents clustering is performed.Then classification is performed to find the input matches with any of the clusters. If it matches the particular cluster file will be listed.Theclassification techniques classify the various file formats and the report is generated as percentage of files available. The graphical representation shows the clear representation of files available in various formats. This method uses least amount of patterns for concept learning compare to other methods such as, Rocchio, Prob, nGram , the concept based models and the most BM25 and SVM models. The proposed model is achieved the high performance and it determined the relevant information what users want. This method reduces the side effects of noisy patterns because the term weight is not only based on term spac e but it also based on patterns. The proper usage of discovered patterns is used to overcome the misinterpretation problem and provide a feasible solution to effectively exploit the vast amount of patterns generated by data mining algorithms. 4. Conclusion Storing huge amount of files in personal computers is a common habit among internet users, which is essentially justified for the following reasons, 1) The information will not always permanent 2) The retrieval of information differs based on the different query search 3) Location same sites for retrieving information is difficult to remember 4) Obtaining information is not always immediate. But these habits have many drawbacks. It is difficult to find when the data is required.In the Internet, the use of searching techniques is now widespread, but in terms of personal computers, the tools are quite limited. The normal â€Å"Search or â€Å"Find† options take several hours to produce the search result. It acquires more time to predict the desire result where the time consumption is high.The proposed system provides accurate result comparing to normal search.All files are indexed and clustered using the efficient k means techniques so the information retrieved in efficient manner. The best and advanced clustering gadget provides optimized time results.Downtime and power consumption is reduced. 5.References [1]K. Aas and L. Eikvil, ‘’Text Categorization: A Survey,’’ Technical Report NR 941, Norwegian Computing Centre, 1999. [2] R. Agarwal and R.Srikanth, ‘’Fast Algorithm for Mining Association Rules in Large Databases, ‘’ Proc. 20th Int’l Conf. Very Large Data Bases(VLDB’94), pp.478-499, 1994. [3] H. Ahonen, O. Heinonen, M. Klemettinen, and A.I. Verkamo, â€Å"Applying Data Mining Techniques for Descriptive Phrase Extraction in Digital Document Collections,† Proc. IEEE Int’l Forum on Research and Technology Advances in Digital Libraries (ADL ’98), pp. 2-11, 1998. [4] R. Baeza-Yates and B. Ribeiro-Neto, Modern Information Retrieval. Addison Wesley, 1999. [5] N. Cancedda, N. Cesa-Bianchi, A. Conconi, and C. Gentile, â€Å"Kernel Methods for Document Filtering,† TREC, trec.nist.gov/ pubs/trec11/papers/kermit.ps.gz, 2002. [6] N. Cancedda, E. Gaussier, C. Goutte, and J.-M. Renders, â€Å"Word- Sequence Kernels,† J. Machine Learning Research, vol. 3, pp. 1059- 1082, 2003. [7] M.F. Caropreso, S. Matwin, and F. Sebastiani, â€Å"Statistical Phrases in Automated Text Categorization,† Technical Report IEI-B4-07- 2000, Instituto di Elaborazionedell’Informazione, 2000. [8] C. Cortes and V. Vapnik, â€Å"Support-Vector Networks,† Machine Learning, vol. 20, no. 3, pp. 273-297, 1995. [9] S.T. Dumais, â€Å"Improving the Retrieval of Information from External Sources,† Behavior Research Methods, Instruments, and Computers, vol. 23, no. 2, pp. 229-236, 1991. [10] J. Han and K.C.-C. Chang, â€Å"Data Mining for Web Intelligence,† Computer, vol. 35, no. 11, pp. 64-70, Nov. 2002. [11] J. Han, J. Pei, and Y. Yin, â€Å"Mining Frequent Patterns without Candidate Generation,† Proc. ACM SIGMOD Int’l Conf. Management of Data (SIGMOD ’00), pp. 1-12, 2000. [12] Y. Huang and S. Lin, â€Å"Mining Sequential Patterns Using Graph Search Techniques,† Proc. 27th Ann. Int’l Computer Software and Applications Conf., pp. 4-9, 2003. [13] N. Jindal and B. Liu, â€Å"Identifying Comparative Sentences in Text Documents,† Proc. 29th Ann. Int’l ACM SIGIR Conf. Research and Development in Information Retrieval (SIGIR ’06), pp. 244-251, 2006. [14] T. Joachims, â€Å"A Probabilistic Analysis of the Rocchio Algorithm with tfidf for Text Categorization,† Proc. 14th Int’l Conf. Machine Learning (ICML ’97), pp. 143-151, 1997. [15] T. Joachims, â€Å"Text Categorization with Support Vector Machines: Learning with Many Relevant Features,† Proc. European Conf. Machine Learning (ICML ’98),, pp. 137-142, 1998. [16] T. Joachims, â€Å"Transductive Inference for Text Classification Using Support Vector Machines,† Proc. 16th Int’l Conf. Machine Learning (ICML ’99), pp. 200-209, 1999. [17] W. Lam, M.E. Ruiz, and P. Srinivasan, â€Å"Automatic Text Categorization and Its Application to Text Retrieval,† IEEE Trans. Knowledge and Data Eng., vol. 11, no. 6, pp. 865-879, Nov./Dec. 1999. [18] D.D. Lewis, â€Å"An Evaluation of Phrasal and Clustered Representations on a Text Categorization Task,† Proc. 15th Ann. Int’l ACM SIGIR Conf. Research and Development in Information Retrieval (SIGIR ’92), pp. 37-50, 1992. [19] D.D. Lewis, â€Å"Feature Selection and Feature Extraction for Text Categorization,† Proc. Workshop Speech and Natural Language, pp. 212-217, 1992. [20] D.D. Lewis, â€Å"Evaluating and Optimizing Automous Text Classification Systems,† Proc. 18th Ann. Int’l ACM SIGIR Conf. Research and Development in Information Retrieval (SIGIR ’95), pp. 246-254, 1995. [21] G. Salton and C. Buckley, â€Å"Term-Weighting Approaches in Automatic Text Retrieval,† Information Processing and Management: An Int’l J., vol. 24, no. 5, pp. 513-523, 1988. [22] F. Sebastiani, â€Å"Machine Learning in Automated Text Categorization,† ACM Computing Surveys, vol. 34, no. 1, pp. 1-47, 2002. [23] Y. Yang, â€Å"An Evaluation of Statistical Approaches to Text Categorization,† Information Retrieval, vol. 1, pp. 69-90, 1999. [24] Y. Yang and X. Liu, â€Å"A Re-Examination of Text Categorization Methods,† Proc. 22nd Ann. Int’l ACM SIGIR Conf. Research and Development in Information Retrieval (SIGIR ’99), pp. 42-49, 1999. : .

Edgar Allan Poe and His Works Essay -- Stories of Edgar Allan Poe

Thesis: Edgar Allan Poe was one of the most influential, yet misunderstood writers in American Literature. I. His Early Life A. His Adoption B. His Education II. His Later Life A. Books Published B. Military Life III. The Conclusion of His Life A. His Marriage B. His Death IV. His Works V. What Others Thought Of Him Edgar Allan Poe was an American writer, known as a poet and critic but most famous as the first master of the short story form, especially tales of the mysterious and macabre. Since his early death, the literary qualities of Poe's writings have been disputed, but his works have remained popular and he influenced many major American and European writers. Born in Boston, Massachusetts, Poe was orphaned in his early childhood and was raised by John Allan, a successful businessman of Richmond, Virginia. Taken by the Allan family to England at the age of six, Poe was enrolled in a private school. Upon returning to the United States in 1820, he continued to study in private schools. He attended the University of Virginia for a year, but in 1827 his foster father, displeased by the young man's drinking and gambling, refused to pay his debts and forced Poe to work as a bookkeeper. (Anderson, 9-22). Poe quit this job, which infuriated John Allan. Poe then left and moved to Boston. There he published his first book, Tamerlane and Other Poems. After this, Poe enlisted in the U.S. Army and served a two-year term. Poe published his second book of poems, Al Araaf in 1829. Poe then reunited with Allan, who obtained him an appointment to the U.S. Military Academy. After only a few months at the academy, Poe was dismissed for neglect of duty, and John Allan disowned him permanently (Anderson, 23-34). P... ...nius." (Regan, 1) While some loved him, others despised him; almost all recognized the value of his works. WORKS CITED Anderson, Madelyn Klein. Edgar Allan Poe: A Mystery. New York: Justin Books, Ltd., 1993 Buranelli, Vincent. Edgar Allan Poe. New York: Twayne Publishers, Inc., 1961 The Collected Poems and Tales of Edgar Allan Poe. New York: The Modern Library, 1992. Complete Stories and Poems of Edgar Allan Poe. Garden City: Doubleday & Company, Inc, 1966. Fisher, Benjamin F. The Cambridge Introduction to Edgar Allan Poe. Cambridge: Cambridge University Press, 2008. Print. Kesterson, David B., ed. Critics on Poe. Coral Gables: University of Miami Press, 1973. Regan, Robert, ed. Poe. A Collection of Critical Essays. Englewood Cliffs: Prentice-Hall, Inc, 1967. Stoudt, Ashley, ed. "An Edgar Allan Poe Reader". State Street Press, 2000.

Male aggression is largely attributed to spousal abuse Essay -- Marria

Missing Tables Male aggression is largely attributed to spousal abuse "The truth is somewhere outside the circle." -ancient proverb The pervasiveness of spousal abuse is traceable from culture to culture. Every culture has a its unique way of dealing with spousal abuse. The fact that spousal abuse is rampant among certain societies and is completely oblivious to others indicates that spousal abuse is politically, socially, and culturally determined. However, common sense validity would imply that male-dominance is the cause of spousal abuse. This is not always true. For instance, in some cultures there is not a clear-cut gender differentiation between males and females. For those cultures, the binary gender line that exists in the Western culture does not apply to them. Incidentally, this raises the question of whether or not there is a "third gender." To delve into the topic of male dominance as attributed to spousal abuse in its comprehensiveness is beyond the scope of this paper; rather, our purpose here is to show how male-dominance affects spousal abuse by taking the cross-cultural approach. Perhaps it is worthwhile to note that the husband-wife relationship is not a linear relationship for all societies. There are some societies where females were forced to take on the role of the husband. Because the husbands were usually away from their homes, the wives became 'heads of the household.' Furthermore, the wives were allowed to beat their husbands at will if they were found of wrongdoing. It absolutely violates and contradicts the husband and wife relationship, which permeates the Western culture. Interestingly, this reversal of gender role between husband and wife proves that the husband-wife r... ...ery) Pearson Correlation 1.000 .032 Sig. (2-tailed) . .801 N 142 63 V754 Wife-Beating Pearson Correlation .032 1.000 Sig. (2-tailed) .801 . N 63 70 Summary: In conclusion, it can be safely established that male aggression plays a major role in motivating spousal abuse. As indicated, in every instance where wife-beating occurs there is a high divorce rate. Furthermore, the significance of these findings show that aggressive behavior is not a biological fact. Briefly, it is not something innate or inborn. The fact that aggression is not grounded in biology suggests that it is culturally and socially constructed. In every society, men and women learn to behave through a process of enculturation. As seen through a case with the Nuer society, women often times take on the role of the husbands. For the westerners, this sometimes comes as a shock

Freedom Fighters Essay

Nelson Mandela was a visionary freedom fighter who brought about the end of an apartheid society and solidified the democratic elections of presidents by majority rule to South Africa. Born in 1918, Mandela’s early introduction to leadership in the Thembu tribe molded his democratic beliefs (â€Å"Nelson Mandela,† 2009). His youth found him exposed to Western culture which ultimately led him to abandon the Thembu culture and relocate to Johannesburg (â€Å"Nelson Mandela,† 2009). It was during his early years in Johannesburg that he explored the many political philosophies that surrounded him. It was also during this time that Mandela began thoughtful observation and contemplation of the struggles of the black men and women in South Africa. Mandela came to the conclusion, â€Å"It was not lack of ability that limited my people, but lack of opportunity† (Sohail, 2005). His profound dissatisfaction with the apartheid society and the oppression of his people eventually led him to join the African National Congress or ANC in 1944 (â€Å"Nelson Mandela,† 2009). In 1948, the Afrikaner dominated National Party established the apartheid customs into law (Sohail, 2005). In response to this the ANC initiated the Campaign for the Defiance of Unjust Laws at the urging of Mandela (Sohail, 2005). This was the turning point for the ANC and the beginning of Mandela’s rise to recognized leader within the ANC. Prior to this campaign the ANC was committed to peaceful negotiations. With Mandela’s convincing they converted to nonviolent protesting with the goal of overthrowing the white minority government and putting an end to the apartheid laws (â€Å"Nelson Mandela,† 2009). These unsuccessful protests were met with violent opposition. It was one such violent encounter that propelled Nelson Mandela and the ANC to adopt violence as a means of protest. In 1960, sixty nine protestors were killed by government police, this act ultimately lead to the development of Umkhonto we Sizwe (Spear of the Nation) by Nelson Mandela (â€Å"Nelson Mandela,† 2009). The Umkhonto we Sizwe was an offshoot of the ANC whose sole purpose was to engage in violent sabotage of the government. It was Nelson Mandela’s activities within the Umkhonto we Sizwe that ultimately l ed to his capture and incarceration. His trial and sentencing captivated a world audience and forced the actions of the South African government into an international spotlight.(â€Å"Nelson Mandela,† 2009). Fully expecting the  death penalty, Mandela rebutted the idea of seeking appeal recognizing the strength of his position in regard to the cause; â€Å"If anything we might serve the cause greater in death as martyrs than we ever could in life† (Sohail, 2005). Nelson Mandela was sentenced to life imprisonment and solidified his standing as a symbolic embodiment of South African’s fight for freedom (â€Å"Nelson Mandela,† 2009). While incarcerated the violence that Mandela birthed continued to escalate over the years. The world continued to pay attention and the United Nations began supporting sanctions against the South African government (Sohail, 2005). Mandela, aware of the violent chaos, began to contemplate a change in strategy. Recognizing that the movement he began was not vast enough to outright overthrow the existing government he began to consider the possibility of negotiations. At the height of the violence and with increasing international pressure t he South African government was ready to negotiate as well. The first of many secret meeting took place in 1988 between President Botha and Nelson Mandela (â€Å"Nelson Mandela,† 2009). While these negotiations failed to produce any compromises they set the precedent for Botha’s successor F.W. de Klerk in 1989. President de Klerk was committed to change and meaningful negotiations. With the help of President de Klerk, Mandela established the foundation on which the ANC and the South African Government would negotiate (Sohail, 2005). President de Klerk overturned several of the apartheid laws and ensured Mandela his freedom. Nelson Mandela, to the celebration of millions, was released on February 11, 1990 (Sohail, 2005). After spending 27 years in prison, Nelson Mandela and F.W. de Klerk mediated the negotiation of the multiparty Convention for a Democratic South Africa (â€Å"Nelson Mandela,† 2009). The culmination of these negotiations was the Record of Understanding signed by Mandela and de Klerk in 1992 establishing a â€Å"freely elected constitutional assembly† (â€Å"Nelson Mandela,† 2009) and the drafting of a new constitution. The first free democratic elections took place on April 27, 1994 (â€Å"Nelson Mandela,† 2009), effectively ending the minority white reign and the apartheid laws. For Mandela’s significant contributions and sacrifices to bring about these social and political changes he was awarded the Nobel Peace Prize in 1993(â€Å"Nelson Mandela,† 2009). Andrew Jackson was a revolutionist and the 7th President of the United States. It was though this pursuit of the United States presidency  that he changed the political landscape; changing the way presidents were elected and solidifying presidential power. He further initiated significant change with the displacement of the Native Americans westward. (Red Hill Productions, 2007) Andrew Jackson was born 1767 in South Carolina. Orphaned by the Revolutionary War at the age of 15, he quickly developed a reputation of being â€Å"hot tempered and violent† (Red Hill Productions, 2007). Yet at the same time, he maintained a strong work ethic and earned a law degree. He relocated to the frontier lands of Tennessee at the age of 20 to serve as a public prosecutor. It was during this period in his life that he first experienced formal politics. Serving as Tennessee’s first Congressman he quickly became disenchanted with the political scene. Frustrated with ineffective committee meetings and what he saw as far reaching corruption, he returned to Tennessee where he became a superior court judge. (Red Hill Productions, 2007) At the urging of his supporters and amid far reaching popularity, Jackson once again entered politics with a bid for the 1822 presidential race. Andrew Jackson was defeated in 1824 despite winning the popular vote. John Quincy Adams was awarded the presidency at the discretion of the sitting House of Representative (â€Å"Andrew Jackson,† 1997). Empowered by what they saw as a corrupt election process where presidents were decided via the political elite and not the will of the common people, Jackson’s supports organized the first Democratic Party (Red Hill Productions, 2007). United under the Democratic Party the common people led a feverish campaign. This campaign culminated in the electing of Andrew Jackson to the presidency in 1828 (Red Hill Productions, 2007). Recognizing the political power of an organized party the Republican Party was realized later in the decade. Originally dubbed â€Å"the National Whig Party† (Red Hill Productions, 2007), the birth of this party laid the foundation for a two party political system that continues to dominate politics today. During Andrew Jackson’s two term presidency he further enacted political change by redefining the role of President within the government. In juxtaposition with the founding fathers, Jackson saw the role of the President as the leader in gov ernment rather than the Congress (Red Hill Productions, 2007). Being the only position in government to be elected by the vast majority of the common people, Andrew Jackson envisioned the presidential responsibility as to â€Å"serve the good of all people† (Red Hill Productions, 2007). With  this responsibility came great power which Jackson wielded with great efficiency. He invoked his executive power and utilized his veto power vehemently (Red Hill Productions, 2007). With this wide sweeping reform and successful transition of political power to the President, Andrew Jackson is credited with being the first modern President (Red Hill Productions, 2007). While serving as President, Andrew Jackson determined to secure westward expansion of the United States enacted even further political and social change with the Indian Removal Act of 1830 (Red Hill Productions, 2007). Jackson was the catalyst that ultimately concluded with the displacement of the Native Americans east of the Mississippi (Red Hill Productions, 2007). Recognizing the significance of westward expansion for the continued success of the United States, Jackson introduced the Indian Removal Act in a message to Congress in 1830 (Red Hill Productions, 2007). This displacement of the Native Americans wou ld open Native American lands for the white Americans to develop and expand westward. The Indian Removal Act was passed by Congress in 1830 (Red Hill Productions, 2007). Despite the Supreme Court ruling in favor of the Cherokee people, Andrew Jackson moved forward with the Indian Removal Act forcing a westward movement of the Cherokee people (Red Hill Productions, 2007). This westward movement was famously termed â€Å"the Trail of Tears† (Red Hill Productions, 2007). This impacted the Creek and Seminole people as well and effectively solidified the expansion of the white farmers and business entrepreneurs on the land west of the Mississippi for the American people (Red Hill Productions, 2007). Andrew Jackson’s contribution of the establishing of political parties and the expansion of presidential power solidifies his legacy of enacting significant political and social change. These contributions continue to remain the foundation of politics in the United States. His Indian Removal Act was an equally significant example of political and social change that allowed the United States to expand westward. This westward expansion firmly cemen ted the continued success of the United States. References Andrew Jackson. (1997). In Biography Reference Bank. Retrieved from http://ehis.ebscohost.com/ehost/delivery?sid=986fb1e9-82c5-4a86-8443-28de1ed235%40sessionmgr112&vid=13&hid=4208 Nelson Mandela. (2009). In Biography