Text REtrieval Conference (TREC)
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Organization Name: Center for Information Research | Run ID: cirtrc82 |
Section 1.0 System Summary and Timing |
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Section 1.1 System Information |
Hardware Model Used for TREC Experiment:Pentium 200 System Use:DEDICATED Total Amount of Hard Disk Storage:12 Gb Total Amount of RAM:48 MB Clock Rate of CPU:200 MHz |
Section 1.2 System Comparisons |
Amount of developmental "Software Engineering":NONE List of features that are not present in the system, but would have been beneficial to have: List of features that are present in the system, and impacted its performance, but are not detailed within this form: |
Section 2.0 Construction of Indices, Knowledge Bases, and Other Data Structures |
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Length of the stopword list:0 words Type of Stemming:MORPHOLOGICAL Controlled Vocabulary:YES Term weighting:YES
Phrase discovery:NO
Type of Spelling Correction:NONE Manually-Indexed Terms:NO Proper Noun Identification:NO Syntactic Parsing:NO Tokenizer:NO Word Sense Disambiguation:YES Other technique:YES Additional comments: |
Section 3.0 Statistics on Data Structures Built from TREC Text |
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Section 3.1 First Data Structure |
Structure Type:OTHER DATA STRUCTURE Type of other data structure used:Thematic presentation of document content Brief description of method using other data structure: Total storage used:1 Gb Total computer time to build:100 hours Automatic process:YES Manual hours required:hours Type of manual labor:NONE Term positions used:YES Only single terms used:NO Concepts (vs. single terms) represented:YES
Type of representation: Auxilary files used:NO
Additional comments:Thesaurus-based thematic structures simulated main, specific document topics and mentioned concepts |
Section 3.2 Second Data Structure |
Structure Type:NONE Type of other data structure used: Brief description of method using other data structure: Total storage used:Gb Total computer time to build:hours Automatic process: Manual hours required:hours Type of manual labor:NONE Term positions used: Only single terms used: Concepts (vs. single terms) represented:
Type of representation: Auxilary files used:
Additional comments: |
Section 3.3 Third Data Structure |
Structure Type:NONE Type of other data structure used: Brief description of method using other data structure: Total storage used:Gb Total computer time to build:hours Automatic process: Manual hours required:hours Type of manual labor:NONE Term positions used: Only single terms used: Concepts (vs. single terms) represented:
Type of representation: Auxilary files used:
Additional comments: |
Section 4.0 Data Built from Sources Other than the Input Text |
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File type:NONE Domain type:DOMAIN INDEPENDENT Total Storage:Gb Number of Concepts Represented:concepts Type of representation:NONE Automatic or Manual:
Type of Manual Labor used:NONE Additional comments: |
File is:NONE Total Storage:Gb Number of Concepts Represented:concepts Type of representation:NONE Additional comments: |
Section 5.0 Computer Searching |
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Average computer time to search (per query): 200 CPU seconds |
Times broken down by component(s): |
Section 5.1 Searching Methods |
Vector space model:NO Probabilistic model:NO Cluster searching:NO N-gram matching:NO Boolean matching:YES Fuzzy logic:NO Free text scanning:NO Neural networks:NO Conceptual graphic matching:YES Other:YES Additional comments: |
Section 5.2 Factors in Ranking |
Term frequency:YES Inverse document frequency:NO Other term weights:YES Semantic closeness:YES Position in document:YES Syntactic clues:YES Proximity of terms:NO Information theoretic weights:NO Document length:YES Percentage of query terms which match:NO N-gram frequency:NO Word specificity:NO Word sense frequency:NO Cluster distance:NO Other:YES Additional comments: |
Section 6.0 Query Construction |
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Section 6.1 Automatically Built Queries for Ad-hoc Tasks |
Topic fields used: Average computer time to build query CPU seconds Term weighting (weights based on terms in topics): Phrase extraction from topics: Syntactic parsing of topics: Word sense disambiguation: Proper noun identification algorithm: Tokenizer: Expansion of queries using previously constructed data structures: Automatic addition of: NONE |
Section 6.2 Manually Constructed Queries for Ad-hoc Tasks |
Topic fields used: TITLE DESCRIPTION NARRATIVE Average time to build query? 5 minutes Type of query builder: SYSTEM EXPERT Tool used to build query: KNOWLEDGE BASE BROWSER Method used in intial query construction? BOOLEAN CONNECTORS Total CPU time for all iterations: seconds Clock time from initial construction of query to completion of final query: 1-5 minutes Average number of iterations: 1 Average number of documents examined per iteration: 0 Minimum number of iterations: 1 Maximum number of iterations: 1 The end of an iteration is determined by: Finish of query expansion Automatic term reweighting from relevant documents: Automatic query expansion from relevant documents: Other automatic methods: Manual methods used: |
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