Text REtrieval Conference (TREC)
System Description

Organization Name: The Open University Run ID: trecES-kmiZhu1
Section 1.0 System Summary and Timing
Section 1.1 System Information
Hardware Model Used for TREC Experiment: ViglenGenie Pentium4
System Use: DEDICATED
Total Amount of Hard Disk Storage: 120 Gb
Total Amount of RAM: 1024 MB
Clock Rate of CPU: 3481 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: Various language models and automatic query expansion techniques.
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: 35 words
Type of Stemming: NONE
Controlled Vocabulary: YES
Term weighting: YES
  • Additional Comments on term weighting: TF/IDF, BM25
Phrase discovery: NO
  • Kind of phrase:
  • Method used: OTHER
Type of Spelling Correction: NONE
Manually-Indexed Terms: NO
Proper Noun Identification: YES
Syntactic Parsing: NO
Tokenizer: YES
Word Sense Disambiguation: NO
Other technique: NO
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:
Brief description of method using other data structure:
Total storage used: 1 Gb
Total computer time to build: 1.2 hours
Automatic process: YES
Manual hours required: hours
Type of manual labor: NONE
Term positions used: YES
Only single terms used: YES
Concepts (vs. single terms) represented: YES
  • Number of concepts represented: 1104
Type of representation: W3C people's names
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: LEXICON
Domain type: DOMAIN SHARED
Total Storage: 0.01 Gb
Number of Concepts Represented: 1104 concepts
Type of representation: RULES
Automatic or Manual: AUTOMATIC
  • Total Time to Build: 2 hours
  • Total Time to Modify (if already built): hours
Type of Manual Labor used: MOSTLY MACHINE BUILT USING MANUAL CORRECTION
Additional comments: Lexicon consists of W3C people's names, variations of these names are constructed by rules and refined by manual corrections.
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): 0.1 CPU seconds
Times broken down by component(s):
Section 5.1 Searching Methods
Vector space model: NO
Probabilistic model: YES
Cluster searching: NO
N-gram matching: NO
Boolean matching: YES
Fuzzy logic: NO
Free text scanning: YES
Neural networks: NO
Conceptual graphic matching: NO
Other: YES
Additional comments: Window based span query, and incremental window sizes in span query search.
Section 5.2 Factors in Ranking
Term frequency: YES
Inverse document frequency: YES
Other term weights: YES
Semantic closeness: YES
Position in document: YES
Syntactic clues: NO
Proximity of terms: YES
Information theoretic weights: NO
Document length: YES
Percentage of query terms which match: YES
N-gram frequency: NO
Word specificity: NO
Word sense frequency: NO
Cluster distance: NO
Other: YES
Additional comments: PageRank based Google ranking of documents are used to determine the importance of these documents on a query topic.
Section 6.0 Query Construction
Section 6.1 Automatically Built Queries for Ad-hoc Tasks
Topic fields used:     TITLE      
Average computer time to build query 0    CPU seconds
Term weighting (weights based on terms in topics): YES
Phrase extraction from topics: NO
Syntactic parsing of topics: NO
Word sense disambiguation: NO
Proper noun identification algorithm: NO
Tokenizer: NO
  • Patterns which were tokenized:
Expansion of queries using previously constructed data structures: NO
  • Comment:
Automatic addition of: NONE
Section 6.2 Manually Constructed Queries for Ad-hoc Tasks
Topic fields used:   TITLE   DESCRIPTION   NARRATIVE   OTHER
Average time to build query? 2   minutes
Type of query builder: DOMAIN EXPERT
Tool used to build query: OTHER LEXICAL TOOL
Method used in intial query construction? PROXIMITY OPERATORS
  • If yes, what was the source of terms? description, narrative, and domain knowledge
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 is determined by:
Automatic term reweighting from relevant documents: NO
Automatic query expansion from relevant documents: NO
  • Type of automatic query expansion: ALL TERMS IN \
Other automatic methods: NO
  • Other automatic methods included:
Manual methods used: NO
  • Type of manual method used: NONE
Send questions to trec@nist.gov

Disclaimer: Contents of this online document are not necessarily the official views of, nor endorsed by the U.S. Government, the Department of Commerce, or NIST.