Experiments on Adaptive Set Intersections for Text Retrieval Systems

2001 ◽  
pp. 91-104 ◽  
Author(s):  
Erik D. Demaine ◽  
Alejandro López-Ortiz ◽  
J. Ian Munro
Keyword(s):  
Text Retrieval ◽  
Retrieval Systems

Experiments with Language-based Aids in Information Retrieval Systems

1988 ◽  
Vol 11 (1-2) ◽  
pp. 33-46 ◽  
Author(s):  
Tove Fjeldvig ◽  
Anne Golden
Keyword(s):  
Information Retrieval ◽  
Text Retrieval ◽  
Considerable Improvement ◽  
Controlled Experiments ◽  
Compound Words ◽  
Search Results ◽  
Retrieval Systems ◽  
Complete Search ◽  
Information Retrieval Systems ◽  
Search Quality

The fact that a lexeme can appear in various forms causes problems in information retrieval. As a solution to this problem, we have developed methods for automatic root lemmatization, automatic truncation and automatic splitting of compound words. All the methods have as their basis a set of rules which contain information regarding inflected and derived forms of words – and not a dictionary. The methods have been tested on several collections of texts, and have produced very good results. By controlled experiments in text retrieval, we have studied the effects on search results. These results show that both the method of automatic root lemmatization and the method of automatic truncation make a considerable improvement on search quality. The experiments with splitting of compound words did not give quite the same improvement, however, but all the same this experiment showed that such a method could contribute to a richer and more complete search request.

The TREC question answering track

2001 ◽  
Vol 7 (4) ◽  
pp. 361-378 ◽  
Author(s):  
ELLEN M. VOORHEES
Keyword(s):  
Large Scale ◽  
Question Answering ◽  
Text Retrieval ◽  
Scale Evaluation ◽  
Retrieval Systems ◽  
Question Answering Systems

The Text REtrieval Conference (TREC) question answering track is an effort to bring the benefits of large-scale evaluation to bear on a question answering (QA) task. The track has run twice so far, first in TREC-8 and again in TREC-9. In each case, the goal was to retrieve small snippets of text that contain the actual answer to a question rather than the document lists traditionally returned by text retrieval systems. The best performing systems were able to answer about 70% of the questions in TREC-8 and about 65% of the questions in TREC-9. While the 65% score is a slightly worse result than the TREC-8 scores in absolute terms, it represents a very significant improvement in question answering systems. The TREC-9 task was considerably harder than the TREC-8 task because TREC-9 used actual users’ questions while TREC-8 used questions constructed for the track. Future tracks will continue to challenge the QA community with more difficult, and more realistic, question answering tasks.

An Architecture for Full Text Retrieval Systems

1990 ◽  
pp. 22-29 ◽  
Author(s):  
Scott C. Deerwester ◽  
Donald A. Ziff ◽  
Keith Waclena
Keyword(s):  
Full Text ◽  
Text Retrieval ◽  
Retrieval Systems ◽  
Full Text Retrieval

Storing text retrieval systems on CD-ROM: compression and encryption considerations

1989 ◽  
Vol 7 (3) ◽  
pp. 230-245 ◽  
Author(s):  
Shmuel T. Klein ◽  
Abraham Bookstein ◽  
Scott Deerwester
Keyword(s):  
Text Retrieval ◽  
Cd Rom ◽  
Retrieval Systems
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