Text REtrieval Conference (TREC)
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Organization Name: Artificial Intelligence Center / SRI | Run ID: srige1 |
Section 1.0 System Summary and Timing |
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Section 1.1 System Information |
Hardware Model Used for TREC Experiment:Sparcs/Ultras System Use:SHARED Total Amount of Hard Disk Storage:1.5 Gb Total Amount of RAM:128 MB Clock Rate of CPU:210 MHz |
Section 1.2 System Comparisons |
Amount of developmental "Software Engineering":SOME 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:NONE Controlled Vocabulary: Term weighting:NO
Phrase discovery:YES
Type of Spelling Correction:NONE Manually-Indexed Terms:NO Proper Noun Identification:YES Syntactic Parsing:YES Tokenizer:YES Word Sense Disambiguation:YES Other technique: Additional comments:We adapted an Information Extraction System for the Routing Task. This involved using IE grammars as queries |
Section 3.0 Statistics on Data Structures Built from TREC Text |
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Section 3.1 First 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:MOSTLY MANUALLY BUILT USING SPECIAL INTERFACES Term positions used:NO Only single terms used:NO Concepts (vs. single terms) represented:YES
Type of representation: Auxilary files used:NO
Additional comments:Given how different our method is from standard IR techniques, it is not clear to us how to answer many of these questions. |
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: 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): 54000 CPU seconds |
Times broken down by component(s): |
Section 5.1 Searching Methods |
Vector space model: Probabilistic model: Cluster searching: N-gram matching: Boolean matching: Fuzzy logic: Free text scanning: Neural networks: Conceptual graphic matching: Other:YES Additional comments:We don't do indexing and hence we don't search indices. |
Section 5.2 Factors in Ranking |
Term frequency:NO Inverse document frequency:NO Other term weights:NO Semantic closeness:NO Position in document:NO Syntactic clues:YES Proximity of terms:NO Information theoretic weights:NO Document length:NO 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:See above |
Section 6.0 Query Construction |
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Section 6.1 Automatically Built Queries for Routing Tasks |
Topic fields used: NONE DESCRIPTION NARRATIVE Average computer time to build query 0 CPU seconds Terms selected from: T Term weighting with weights based on terms in: Phrase extraction from topics: Syntactic parsing of topics: Word sense disambiguation: Proper noun identification algorithm: Tokenizer: Additional comments: Expansion of queries using previously constructed data structures: Automatic addition of using information from |
Section 6.2 Manually Constructed Queries for Routing Tasks |
Topic fields used: Average time to build query? minutes Type of query builder: Tool used to build query: Data used for building query from: Addition of terms not included in topic: Total CPU time for all iterations: seconds Clock time from initial construction of query to completion of final query: minutes Average number of iterations: Average number of documents examined per iteration: Minimum number of iterations: Maximum number of iterations: The end of an iteration was determined by: Automatic term reweighting from relevant documents: Automatic query expansion from relevant documents: Other automatic methods: Manual methods used: |
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