Text REtrieval Conference (TREC)
System Description

Organization Name: Rutgers University Run ID: rutLADw
Section 1.0 System Summary and Timing
Section 1.1 System Information
Hardware Model Used for TREC Experiment: SuperSPARC II
System Use: DEDICATED
Total Amount of Hard Disk Storage: 9 Gb
Total Amount of RAM: 483 MB
Clock Rate of CPU: 60 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
Length of the stopword list: 631 words
Type of Stemming: SMART
Controlled Vocabulary: NO
Term weighting: NO
  • Additional Comments on term weighting:
Phrase discovery: NO
  • Kind of phrase:
  • Method used: OTHER
Type of Spelling Correction: NONE
Manually-Indexed Terms: NO
Proper Noun Identification: NO
Syntactic Parsing: NO
Tokenizer: NO
Word Sense Disambiguation: NO
Other technique: YES
Additional comments:
Section 3.0 Statistics on Data Structures Built from TREC Text
Section 3.1 First Data Structure
Structure Type: INVERTED INDEX
Type of other data structure used: binary vector
Brief description of method using other data structure: logical analysis of data
Total storage used: 0.5 Gb
Total computer time to build: 12 hours
Automatic process: NO
Manual hours required: hours
Type of manual labor: NONE
Term positions used: NO
Only single terms used: YES
Concepts (vs. single terms) represented: NO
  • Number of concepts represented:
Type of representation: inverted index
Auxilary files used: NO
  • Type of auxilary files used:
Additional comments:
Section 3.2 Second 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:
  • Number of concepts represented:
Type of representation:
Auxilary files used:
  • Type of 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:
  • Number of concepts represented:
Type of representation:
Auxilary files used:
  • Type of auxilary files used:
Additional comments:
Section 4.0 Data Built from Sources Other than the Input Text
Internally-built Auxiliary File

File type: NONE
Domain type: DOMAIN INDEPENDENT
Total Storage: Gb
Number of Concepts Represented: concepts
Type of representation: NONE
Automatic or Manual:
  • Total Time to Build: hours
  • Total Time to Modify (if already built): hours
Type of Manual Labor used: NONE
Additional comments:
Externally-built Auxiliary File

File is: NONE
Total Storage: Gb
Number of Concepts Represented: concepts
Type of representation: NONE
Additional comments:
Section 5.0 Computer Searching
Average computer time to search (per query): 60 CPU seconds
Times broken down by component(s):
Section 5.1 Searching Methods
Vector space model: YES
Probabilistic model: NO
Cluster searching: NO
N-gram matching: NO
Boolean matching: NO
Fuzzy logic: NO
Free text scanning:
Neural networks: NO
Conceptual graphic matching: NO
Other: NO
Additional comments:
Section 5.2 Factors in Ranking
Term frequency: YES
Inverse document frequency: YES
Other term weights: NO
Semantic closeness: NO
Position in document: NO
Syntactic clues: NO
Proximity of terms:
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: NO
Additional comments:
Section 6.0 Query Construction
Section 6.1 Automatically Built Queries for Routing Tasks
Topic fields used:  NONE        
Average computer time to build query 3600    CPU seconds
Terms selected from: ALL TRAINING DOCUMENTS
Term weighting with weights based on terms in: ALL TRAINING DOCUMENTS
Phrase extraction from topics: NONE
Syntactic parsing of topics: NONE
Word sense disambiguation: NONE
Proper noun identification algorithm: NONE
Tokenizer: NONE
Additional comments:
Expansion of queries using previously constructed data structures: NO
  • Comment:
Automatic addition of NONE 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: OTHER
Tool used to build query: NONE
Data used for building query from: TRAINING TOPICS
Addition of terms not included in topic:
  • The source of terms was:
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:
  • Type of automatic query expansion: ALL TERMS IN \
Other automatic methods:
  • Other automatic methods included:
Manual methods used:
  • Type of manual method used: NONE
Send questions to trec@nist.gov

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