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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 20 of 20 1 PREDICTING MUSIC GENRE PREFERENCES BASED ON ONLINE COMMENTS Sinclair, Andrew J In: Master's Theses (2014) BASE Show details 2 Why Microsoft Arabic Spell checker is ineffective Neme, Alexis Amid In: ISSN: 0851-6774 ; Linguistica Communicatio ; https://hal.archives-ouvertes.fr/hal-01081965 ; Linguistica Communicatio, http://www.al-erfan.com/, 2014, Arabic Language in Information Technology, 16, pp.55 ; http://www.al-erfan.com/ (2014) BASE Show details 3 Unsupervised Knowledge-based Word Sense Disambiguation: Exploration & Evaluation of Semantic Subgraphs ... Manion, Steve Lawrence. - : University of Canterbury. Department of Mathematics & Statistics, 2014 BASE Show details 4 Entity Information Extraction using Structured and Semi-structured resources ... Unkn Unknown. - : Temple University. Libraries, 2014 BASE Show details 5 The Role of Emotional and Facial Expression in Synthesised Sign Language Avatars Smith, Robert G In: Other Resources (2014) BASE Show details 6 Perception Based Misunderstandings in Human-Computer Dialogues Schütte, Niels; Kelleher, John D.; Mac Namee, Brian In: Articles (2014) BASE Show details 7 The Effect of Sensor Errors in Situated Human-Computer Dialogue Schütte, Niels; Kelleher, John D.; Mac Namee, Brian In: Conference papers (2014) BASE Show details 8 Exploring issues in lexical acquisition using Bayesian modelling Börschinger, Benjamin. - : Sydney, Australia : Macquarie University, 2014 BASE Show details 9 ALCIDE: An online platform for the Analysis of Language and Content In a Digital Environment Sara, Tonelli; Giovanni, Moretti; Sprugnoli, R (orcid:0000-0001-6861-5595). - : Pisa University Press srl, 2014. : country:ITA, 2014. : place:Pisa, 2014 BASE Show details 10 Lines of succession in an English ballad tradition: the publishing history and textual descent of The Wandering Jew’s chronicle Howe, Christopher J; Bergel, Giles; Windram, Heather F. - 2014 BASE Show details 11 Unsupervised Knowledge-based Word Sense Disambiguation: Exploration & Evaluation of Semantic Subgraphs Manion, Steve Lawrence. - : University of Canterbury. Department of Mathematics & Statistics, 2014 BASE Show details 12 Word vector-space embeddings of natural language data over time Lala, Chiraag. - : The University of Edinburgh, 2014 BASE Show details 13 An Interpretation of Sheldon Klein's Four Valued Analogical Transformational Operator Midmore, Roger. - : University of Wisconsin-Madison Department of Computer Sciences, 2014 BASE Show details 14 Investigating the Language of Engineering Education Variawa, Chirag. - 2014 BASE Show details 15 Identification of Informativeness in Text using Natural Language Stylometry Shams, Rushdi In: Electronic Thesis and Dissertation Repository (2014) Abstract: In this age of information overload, one experiences a rapidly growing over-abundance of written text. To assist with handling this bounty, this plethora of texts is now widely used to develop and optimize statistical natural language processing (NLP) systems. Surprisingly, the use of more fragments of text to train these statistical NLP systems may not necessarily lead to improved performance. We hypothesize that those fragments that help the most with training are those that contain the desired information. Therefore, determining informativeness in text has become a central issue in our view of NLP. Recent developments in this field have spawned a number of solutions to identify informativeness in text. Nevertheless, a shortfall of most of these solutions is their dependency on the genre and domain of the text. In addition, most of them are not efficient regardless of the natural language processing problem areas. Therefore, we attempt to provide a more general solution to this NLP problem. This thesis takes a different approach to this problem by considering the underlying theme of a linguistic theory known as the Code Quantity Principle. This theory suggests that humans codify information in text so that readers can retrieve this information more efficiently. During the codification process, humans usually change elements of their writing ranging from characters to sentences. Examples of such elements are the use of simple words, complex words, function words, content words, syllables, and so on. This theory suggests that these elements have reasonable discriminating strength and can play a key role in distinguishing informativeness in natural language text. In another vein, Stylometry is a modern method to analyze literary style and deals largely with the aforementioned elements of writing. With this as background, we model text using a set of stylometric attributes to characterize variations in writing style present in it. We explore their effectiveness to determine informativeness in text. To the best of our knowledge, this is the first use of stylometric attributes to determine informativeness in statistical NLP. In doing so, we use texts of different genres, viz., scientific papers, technical reports, emails and newspaper articles, that are selected from assorted domains like agriculture, physics, and biomedical science. The variety of NLP systems that have benefitted from incorporating these stylometric attributes somewhere in their computational realm dealing with this set of multifarious texts suggests that these attributes can be regarded as an effective solution to identify informativeness in text. In addition to the variety of text genres and domains, the potential of stylometric attributes is also explored in some NLP application areas---including biomedical relation mining, automatic keyphrase indexing, spam classification, and text summarization---where performance improvement is both important and challenging. The success of the attributes in all these areas further highlights their usefulness. Keyword: Artificial Intelligence and Robotics; Computational Linguistics; Data Mining; Machine Learning; Natural Language Processing; Statistical Models; Stylometry; Text Analytics URL: https://ir.lib.uwo.ca/etd/2365 https://ir.lib.uwo.ca/cgi/viewcontent.cgi?article=3753&context=etd BASE Hide details 16 Cosine Similarity for Article Section Classification: Using Structured Abstracts as a Proxy for an Annotated Corpus Bugorski, Arthur T In: Electronic Thesis and Dissertation Repository (2014) BASE Show details 17 Egyptian Arabic Plurals in Theory and Computation Winchester, Lindley In: Theses and Dissertations--Linguistics (2014) BASE Show details 18 An empirical study of semantic similarity in WordNet and Word2Vec Handler, Abram In: University of New Orleans Theses and Dissertations (2014) BASE Show details 19 COMPUTATIONAL COMMUNICATION INTELLIGENCE: EXPLORING LINGUISTIC MANIFESTATION AND SOCIAL DYNAMICS IN ONLINE COMMUNICATION Xu, Xiaoxi In: Doctoral Dissertations (2014) BASE Show details 20 Computational Modeling of Learning Biases in Stress Typology Staubs, Robert D In: Doctoral Dissertations (2014) BASE Show details

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