Text REtrieval Conference (TREC)
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Organization Name: Siemens AG | Run ID: teklis6 |
Section 1.0 System Summary and Timing |
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Section 1.1 System Information |
Hardware Model Used for TREC Experiment:PC Pentium Pro System Use:SHARED Total Amount of Hard Disk Storage:9 Gb Total Amount of RAM:128 MB Clock Rate of CPU:200 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:- usage of topic descriptions for learning - categorization of paragraphs - word context for word sense disambiguation 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:NO Term weighting:YES
Phrase discovery:NO
Type of Spelling Correction:NONE Manually-Indexed Terms: Proper Noun Identification: Syntactic Parsing: Tokenizer:YES Word Sense Disambiguation: Other technique:YES Additional comments:other technique: statistical word pair recognition |
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:Dictionary Brief description of method using other data structure: Total storage used:0.02 Gb Total computer time to build:8 hours Automatic process:YES Manual hours required:hours Type of manual labor:NONE Term positions used:NO Only single terms used:YES Concepts (vs. single terms) represented:NO
Type of representation: Auxilary files used:YES
Additional comments: |
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:LEXICON 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:We used an existing small lexicon (85K compressed) with common irregular words for stemming. |
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): CPU seconds |
Times broken down by component(s): |
Section 5.1 Searching Methods |
Vector space model: Probabilistic model:YES Cluster searching: N-gram matching: Boolean matching: Fuzzy logic:YES Free text scanning: Neural networks: Conceptual graphic matching: Other: Additional comments:Since teklis is a categorization system it's not possible to give a search time per query. It processes about 1500 words per sec. |
Section 5.2 Factors in Ranking |
Term frequency: Inverse document frequency: Other term weights:YES Semantic closeness: Position in document: Syntactic clues: Proximity of terms: Information theoretic weights: Document length:YES Percentage of query terms which match: N-gram frequency: Word specificity: Word sense frequency:YES Cluster distance: Other: Additional comments:We used a correlation measure as term weight |
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