First Text Retrieval Conference (Trec-1): Proceedings
DIANE Publishing, 1993 - 518 pages
Held in Gaithersburg, MD, Nov. 4-6, 1992. Evaluates new technologies in information retrieval. Numerous graphs, tables and charts.
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15 docs 30 docs algorithm analysis Averages False Alarm Averages Precision Average Boolean build approximate number build query CLARIT collection concepts context vectors data structures database disk docs at 15 docs at 200 docs at 30 Document Level Averages documents retrieved evaluation genetic algorithm information retrieval inverted file inverted index keywords knowledge base Level Averages Precision Level Averages Recall manual matching methods natural language processing Num_queries number of documents number of hours parsing performance phrases Precision Average precision query construction query expansion query individuals query terms query vector ranking Recall Level Averages relevance feedback relevance judgments relevant documents ROC Averages False routing queries semantic Statistics Run number stemming stemming algorithms stopword storage megabytes Summary Statistics Summary Statistics Run syntactic techniques term weighting Text REtrieval Conference thesaurus topic statement total computer total cpu seconds TREC experiments vector space model word sense disambiguation WordNet
Page 297 - The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Defense Advanced Research Projects Agency or the US Government.
Page 351 - In recognition of the contributions of all mothers to their families and to the Nation, the Congress, by a joint resolution approved May 8, 1914 (38 Stat. 770), has designated the second Sunday in May each year as Mother's Day and requested the President to call for its appropriate observance.
Page 87 - Extending the Boolean and Vector Space Models of Information Retrieval with P-Norm Queries and Multiple Concept Types.
Page 136 - Harshman, RA (1990). Indexing by latent semantic analysis. Journal of the Society for Information Science 41, 6, 391^07.
Page 20 - Report on the Need for and Provision of an "Ideal" Information Retrieval Test Collection, British Library Research and Development Report 5266, Computer Laboratory, University of Cambridge.
Page 150 - GW and Harshman, RA Indexing by latent semantic analysis. Journal of the Society for Information Science, 1990, 41(6), 391-407.
Page 151 - The term-by-document matrix is decomposed into a set of k, typically 100 to 300, orthogonal factors from which the original matrix can be approximated by linear combination. Instead of representing documents and queries directly as sets of independent words.
Page 200 - A brief overview can be found in . Essentially, the semantic modeling approach identified concepts useful in talking informally about the real world. These concepts included the two notions of entities (objects in the real world) and relationships among entities (actions in the real world). Both entities and relationships have properties. The properties of entities are often called attributes. There are basic or surface level attributes for entities in the real world. Examples of surface level...
Page 60 - In choosing a term weighting system, low weights should be assigned to high-frequency terms that occur in many documents of a collection, and high weights to terms that are important in particular documents but unimportant in the remainder of the collection. The weight of terms that occur rarely in a collection is relatively unimportant, because such terms contribute little to the needed similarity computation between different texts.
Page viii - There was a large variation of retrieval techniques reported on, including methods using automatic thesauri, sophisticated term weighting, natural language techniques, relevance feedback, and advanced pattern matching. As results had been run through a common evaluation package, groups were able to compare the effectiveness...