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Testing time: for a new document, find the most similar prototype ... At the test time, instead of using all the training instances, use only prototype vectors. ...
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Bagging ... Using the 'bag of words' representation, where each word is ... Compared Bagging, Feature Selection, Subsample, Random Bundling and Rocchio Bundling ...
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CHI) Mutual Information (MI) Term Strength (TS) 11. Classification Algorithms ... Support Vector Machine (SVM) Voting algorithms. 12. Rocchio's Algorithm ...
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CHI) or. A: w and Cj B: w and not Cj. C: not w and Cj D: not w and not Cj. Mutual ... Support Vector Machine (SVM) Voting algorithms. 13. Rocchio's Algorithm ...
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Universit degli Studi di Siena. Dottorato di Ricerca in Ingegneria ... Leonardo Rigutini Dipartimento Ingegneria ... used the Winnow (ANN) and Rocchio ...
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An EM based training algorithm. for. Cross-Lingual Text Categorization ... They used the Winnow (ANN) and Rocchio algorithms and compared the results with ...
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Mara Hancock, UC Berkeley. Kirk Alexander, UC Davis. Rose Rocchio, UCLA. Faust Gorham, UC Merced ... a group of people and resources supporting the code and ...
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Processing of large document collections. Part 2 (Text categorization) Helena Ahonen-Myka ... e.g. two types of Sports news: boxing and rock-climbing ...
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Automatic Text Classification through Machine Learning David W. Miller Semantic Web Spring 2002 Department of Computer Science University of Georgia
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Introduction to Information Retrieval Introduction to Information Retrieval CS276: Information Retrieval and Web Search Text Classification 1 Chris Manning, Pandu ...
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Title: Mining and Summarizing Customer Reviews Author: Preferred Customer Last modified by: Bing Liu Created Date: 6/21/2004 3:23:40 AM Document presentation format
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Crawler. Outline. User's Relevance feedback. How VSM utilizes the relevance feedback ... Or, the system can guess the user's relevance feedback by monitoring ...
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1. CS 391L: Machine Learning. Text Categorization. Raymond J. Mooney. University of Texas at Austin ... lottery. win. Friday. exam. computer. May. PM. test ...
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tf x idf. Recall the Zipf distribution. Want to weight terms ... in the collection offer little discriminating power. CPSC 404 Laks V.S. ... TF x IDF ...
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... Science. Carnegie Mellon University. LM Applied to IR ... modeling of both queries ... Retrieval as a sequence of presenting decisions. Application of ...
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Title: Determining, Creating, and Encoding Semantic, Domain-Specific, and Domain-Independent Knowledge for Sentiment Analysis Author: Patricia Ordonez
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Information Retrieval and Web Search Adopted from Slides from Bin Liu @UIC & Christopher Manning and Prabhakar Raghavan @ Stanford Search using inverted index Given a ...
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W. Bartkiewicz Wprowadzenie do budowy us ug informacyjnych Wyk ad 5. Klasyfikacja dokument w tekstowych Filtrowanie, rekomendacja i kategoryzacja
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Title: Mining and Summarizing Customer Reviews Author: Preferred Customer Last modified by: xwu Created Date: 6/21/2004 3:23:40 AM Document presentation format
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Mining unstructured data for meaning Toby Mostyn
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Most text mining tasks use Information Retrieval (IR) ... Okapi relevance method ... The Okapi method and its variations are popular techniques in this setting. ...
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Lecture 8: Probabilistic IR and Relevance Feedback SIMS 202: Information Organization and Retrieval Prof. Ray Larson & Prof. Marc Davis UC Berkeley SIMS
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CS276 Information Retrieval and Web Search Christopher Manning and Prabhakar Raghavan Lecture 9: Query expansion
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In relevance feedback, the user marks a number of documents as relevant/nonrelevant. We then try to use this information to return better search results. ...
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CS276 Information Retrieval and Web Search Pandu Nayak and Prabhakar Raghavan Lecture 9: Query expansion * SMART: Cornell (Salton) IR system of 1970s to 1990s.
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Vector operations to capture boolean query conditions ... 'The art of finding groups in data.' -- Kaufmann and Rousseeu. 23. Problems with Vector Space ...
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Implementing Cross-Language Text Retrieval Systems for Large-scale text Collections and the World Wide Web Mark W. Davis and William C.Ogden AAAI 1997
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Text Mining Dr Eamonn Keogh Computer Science & Engineering Department University of California - Riverside Riverside,CA 92521 eamonn@cs.ucr.edu Text Mining ...
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1. Relevance Feedback and other Query Modification Techniques. ????: ????????? ... [AF77] Attar, R. and Fraenkel, A. S., 'Local Feedback in Full-Text Retrieval ...
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IFT6255: Information Retrieval A synthesis, analysis and comparison of text classification algorithms Ligen Wang Jing Bai Overview Definition of text classification ...
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International Conference On Computational Linguistics. ... combination method showed middle values between the Cen(S) and Sim(S,T) curves ...
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... Strategy: Find similar users and predicted (weighted) average of user ratings ... the user to rate each article read from one to five. Learns a user profile ...
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Nancy Abady Ferdinand Alvaro Keith Archer. Christina Baker Jeremy Balina ... Robert Delfausse Thomas Dugan. Lester Kostick Joan O'Connor. Rosemary Romano Roger Wesby ...
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Semi-supervised learning: yi is unknown for most instances. The ... Arc-emission HMM (Mealy machine): The probability depends on (from-state, to-state) pair. ...
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MARS: Applying Multiplicative Adaptive User Preference Retrieval to Web Search Zhixiang Chen & Xiannong Meng U.Texas-PanAm & Bucknell Univ.
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For each category, compute a prototype vector by summing the vectors of the ... Assign test documents to the category with the closest prototype vector based on ...
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References Chapter 5 (Query Operations) in Baeza-Yates and Ribeiro-Neto, Modern Information Retrieval. A. Singhal and F. Pereira, ...
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ni is number of docs in corpus containing term ki. Computing Similarity (Term ... Ideal query is approximated by shared terms in relevant documents. Assumptions ...
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Web-based Information Architectures Jian Zhang
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Commercial successes and failures. Caveats. Why we have survived. ... 1983 - Okapi started. 1985 RIAO-1. 1986 CvR logic model. 1990 Deerwester et al,LSI paper ...
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CS276A Information Retrieval Lecture 9 Recap of the last lecture Results summaries Evaluating a search engine Benchmarks Precision and recall Example 11pt precision ...
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The Information Retrieval Cycle Upcoming Topics Different Types ... learning capabilities of the system Playing with different types of query operators Reverse ...
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( ) Partially Supervised Learning ( ) 1011WM05 TLMXM1A Wed 8,9 (15:10-17:00) U705 Min-Yuh Day Assistant Professor
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... based medicine criteria exist only for a small fraction of medicine ... Optimal Combination of Existing Resources (Corpus, General Dictionary, Thesaurus: MeSH) ...
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For i from 1 to n let pi = 0, 0,...,0 (init. prototype vectors) ... Build feature vectors: 0/1 presence/absence of a keyword ...
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MAP (maximum a posteriori) decision rule: classify (x) = classify (f1, .., fd) = argmaxc p(c|x) ... For each position, P(w=a)=p1, P(w=b)=p2 and P(w=c)=p3. ...
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Title: CSE 2340 Lectures Author: Gheorghe Spiride Last modified by: Velardi Paola Created Date: 2/12/2002 11:22:55 PM Document presentation format
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which documents contain an optimistic view on the ... automatic indexing for Boolean IR systems. web search engines (grouping search results, web directories, ...
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'car wash', 'truck wash' If you want to buy a car 'auto quotes' 'auto ... 'auto wash' vs 'car wash' Lack of discrimination 'auto quotes' vs 'auto sale quotes' ...
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Backgammon. Pole balancing. Driving a car. Flying a helicopter. Robot navigation. 5 ... Checkers board positions labeled with correct move. Road images with ...
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Bing Liu. CS Department, UIC. 1. Chapter 8: Semi-Supervised Learning ... Bing Liu. CS Department, UIC. 20. Incorporating unlabeled Data with EM (Nigam et al, 2000) ...
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Local analysis: derive information from retrieved document set ... Use click through counts to order URLs for subsequent submissions of Q ...
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Relation to Expert Finding. Email message (long) query. Email addresses experts ... Instead...write-then-address behavior. Related Work. Expert finding in Email ...
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Dr. Rafail Ostrovsky, Telcordia Technologies, -algorithms ... Algorithm detects a new class. Human analyst labels it; determines its significance ...
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Analysis of sentiment syntagma using dependency tree Serge B. Potemkin Moscow State University potemkin@philol.msu.ru * Review info from blogs, newsgroups, etc ...
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Statistical Classification for Gene Analysis based on Micro-array ... Researcher have done experiments and constructed bayesian networks from micro-array data. ...
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