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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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... Edie Rasmussen, (Robert Korfage, Peter Willett) ... Fidel, (Ed Fox, Peter Ingwersen) ... Ellen Voorhees, (Nick Belkin, Peter Willett, Desai Narasimhulu) ...
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CS276A Text Retrieval and Mining Lecture 10 Recap of the last lecture Improving search results Especially for high recall. E.g., searching for aircraft so it matches ...
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Investigation into Internet search technology Thomas Carnell South Bank University, London SE1 0AA, UK carnelta@sbu.ac.uk
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Information Retrieval Lecture 11 Probabilistic IR * * In addition to the document independence assumption on previous , we have a term independence ...
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Sneath and Sokal, Numerical Taxonomy (1973) Jardine and Sibson, Mathematical Taxonomy (1971) ... Duality is the key. Class definition! CvR. 9. Static Clustering ...
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matched to data? How relevant is the result. to the query ? Document collection ... for provable properties for PI based IR. Another look at the same ...
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Title: Text Data Mining Author: hearst Last modified by: SIMS Network Administrator Created Date: 9/22/1997 12:59:07 AM Document presentation format
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Data: DB IR, XML, text, images. Users: Expert, Naive. Communities. Strategy ... Test data/collections. Efficiency. What Next? Example Hard Problems. Visualisation ...
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Spring 03. CIS392 Lecture 1. 1. NJIT CIS 392. Text Processing, Retrieval, and Mining ... 6. Routing and Filtering (try msnbc.com, or ACM digital library bookshelf. ...
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... web Using extrapolation methods Random queries and their coverage by different search engines Overlap between search engines HTTP requests to random IP ...
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In person: GITC 5502, 12-1pm, Monday; 5-5:45pm, Friday. By phone: (973) 596 5285 ... 6. Routing and Filtering (try msnbc.com, or ACM digital library bookshelf. ...
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Ahmet Selman Bozkir. Introduction to conditional, total ... One answer is the Okapi formulae (S. Robertson) Combine to find document relevance probability ...
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of relevant docs in the collection. 1.0. 1.0. Recall. Precision. 1.0. 1.0. Recall. Precision ... How closely do the ranks of the retrieved documents ...
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Title: PowerPoint Presentation Author: Valued Gateway Client Last modified by: a Created Date: 8/26/2002 7:08:49 AM Document presentation format: Ekran G sterisi
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Lecture 11: Evaluation Intro Principles of Information Retrieval Prof. Ray Larson University of California, Berkeley School of Information Today Evaluation of IR ...
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Lecture 12: Evaluation Cont. Principles of Information Retrieval Prof. Ray Larson University of California, Berkeley School of Information Overview Evaluation of IR ...
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Okapi BM25. Assume that. Factor in the term frequencies (tf) and document ... For example, the Okapi BM25 term weighting formulas have been very successful, ...
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Title: PowerPoint Presentation Author: Valued Gateway Client Last modified by: Marc Davis Created Date: 9/3/2002 3:52:45 AM Document presentation format
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Part I: Survey. Alexander Dekhtyar. department of Computer Science. University of Maryland ... Easier to read than most other surveys. ...
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Cluster analysis a technique that allows the identification of ... Di,Dj = document vector. C = Di Dj = vector containing common terms of the document vectors ...
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DOK 324: Principles of Information Retrieval Hacettepe University Department of Information Management
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Information Retrieval Lecture 7 Recap of the last lecture Vector space scoring Efficiency considerations Nearest neighbors and approximations This lecture Evaluating ...
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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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Department of Computing Science, University of Glasgow. October, 21th - 2002 ... Qualitative part: Directed Acyclic Graph. G=(V,E): V (Nodes) Random variables, and ...
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... formula derived from a probabilistic model under the 2-Poisson assumption. ... Two natural assumptions: H(D): Hidden terms in document D ...
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'something that (1) is represented by a set of symbols, (2) has some structure, ... SMART, InQuery, Okapi, ZPRISE, Panoptics, Lemur. Web search engine designers ...
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I-Know 2005. Experiments in clustering homogeneous XML documents to ... ALADIN Bang Estime IDOPT Macs Mathfi Micmac OMEGA Opale Caiman Calvi Smash. 4b. Sigma2 ...
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Library book checkout patterns. Incoming Web Page Requests (Nielsen) ... One measure: Mutual Information (Church and Hanks 89) ...
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Using XML Logical Structure to Retrieve (Multimedia) Objects. Zhigang ... Queen Mary, University of London. Outline. Motivation. Test Collections. Related Work ...
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Ecological Statistics and Visual Grouping
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Title: CS276A Text Information Retrieval, Mining, and Exploitation Author: Christopher Manning Last modified by: admin Created Date: 10/22/2002 6:34:39 AM
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... Today The Language Model Approach to IR Basic query generation ... Model) Traditional generative model: ... motivated probabilistic model of ...
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Gaining Tax Exempt Status for Your Nonprofit Organization. Lindy Turner, Coordinator ... Fifth of of ten sessions on Building an Effective Nonprofit Organization ...
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School of Computing, Dublin City University. Recherche financ e par ... Measure for Document Retrieval and Labeling Assistance, Cancun, Mexico, Proc. ...
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Five different training sets (Russian, German, French, Spanish, and All Languages ... Lucy Kuntz, Paul O'Leary & Ralph Moon, 'Cheshire II: Designing a Next-Generation ...
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Annotations s mantiques pour la localisation de ressources par des graphes tiquet s Michel Chein LIRMM (Universit Montpellier 2 et CNRS )
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The anatomy of a large-scale hypertextual web search engine. ... House: modeling user's needs and search strategies as a basis for system design ...
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Avalia o De Sistemas De Recupera o De Informa o (RI): Panor mica E Reflex es Rachel Virg nia Xavier Aires 27 de junho de 2002
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The Role of Document Structure in Querying, Scoring and Evaluating XML Full-Text Search Sihem Amer-Yahia AT&T Labs Research - USA Database Department
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Bilgi Eri im Sorunu Ya ar Tonta Hacettepe niversitesi tonta@hacettepe.edu.tr yunus.hacettepe.edu.tr/~tonta/ BBY220 Bilgi Eri im lkeleri Plan Bilgi art ...
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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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Applying Evolutionary Computation Techniques to Web ... Keyword1. Randomly. generated. Chromosome. W1 W2 select. Keyword1. 38. HGA for Web Search (cont. ...
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How big is the lexicon V? Grows (but more slowly) with corpus size. Empirically okay model: ... Query car tyres car tyres automobile tires. Can expand index ...
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There are many search engines on the market, which one is best for your need? ... (b) Okapi Similarity Measurement(Okapi) (c) Cover Density Ranking(CDR) ...
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CS276 Information Retrieval and Web Search Christopher Manning and Prabhakar Raghavan Lecture 9: Query expansion
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difficult to characterize in terms of the type of ambiguity being modeled ... represent a real ambiguity class pair (met in the training corpus) ...
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Implicit Links: MEDLINE records. PMID- 10506108 ... MEDLINE abstracts. Result Set ... 48753 judged MEDLINE documents for 50 queries from the TREC Genomics Track 2004. ...
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Keyword-based IR and early conceptual approaches. Context and concepts in modern topical IR ... Matching the query against document clusters (Willet 1988) ...
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p2p vs distribute database system vs BestPeer vs PeerDB. ... protein name (e.g., Kinases, annexin) or after the species (e.g, human,zebrafish) ...
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Available: http://www.sims.berkeley.edu/research/projects/how ... 5 Megabytes: The complete works of Shakespeare. 2 Megabytes: A high-resolution photograph. ...
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used for multi-lingual retrieval. How exactly SVD works? Indexing - Detailed outline ... secondary key / multi-key indexing. spatial access methods. fractals ...
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Lecture 4: IR System Elements (cont) Principles of Information Retrieval Prof. Ray Larson University of California, Berkeley School of Information
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A Soccer video topology was generated utilising domain ... Advert. Studio. Game. Correct Class. 94.9. 95.9. 95.6. 95.4. 3.7. 3.0. 3.4. 3.5. 1.4. 1.1. 1.0. 1.1 ...
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Chunking is the indentifying and classifying non-overlapping portions of a ... Accuracy of chunking systems can be evaluated using techniques from information ...
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