System Summary and Timing
  Organization Name: University of Maryland College Park
  List of Run ID's: umcpa1

  Construction of Indices, Knowledge Bases, and other Data Structures 

    Methods Used to build Data Structures 

    - Length (in words) of the stopword list: 571 
    - Controlled Vocabulary?: No 
    - Stemming Algorithm: Porter              
      - Morphological Analysis: No 
    - Term Weighting: ltc 
    -  Phrase Discovery?: No             
    -  Syntactic Parsing?: No 
    -  Word Sense Disambiguation?: No 
    -  Heuristic Associations (including short definition)?: No 
    -  Spelling Checking (with manual correction)?: No 
    -  Spelling Correction?: No 
    -  Proper Noun Identification Algorithm?: No 
    -  Tokenizer?: No             
    -  Manually-Indexed Terms?: No 
    -  Other Techniques for building Data Structures: No 

    Statistics on Data Structures built from TREC Text

    - Inverted index           
      - Run ID: umcpa1 
      - Total Storage (in MB): 23 
      - Total Computer Time to Build (in hours): 1 
      - Automatic Process? (If not, number of manual hours): Yes 
      - Use of Term Positions?: No 
      - Only Single Terms Used?: Yes 
    - Clusters           
    - N-grams, Suffix arrays, Signature Files           
    - Knowledge Bases            
      - Use of Manual Labor                  
    - Special Routing Structures           
    - Other Data Structures built from TREC text           

    Data Built from Sources Other than the Input Text

    -  Internally-built Auxiliary File            
      - Use of Manual Labor                   
    -  Externally-built Auxiliary File            

  Query construction

    Automatically Built Queries (Ad-Hoc)

    - Average Computer Time to Build Query (in cpu seconds): 5 
    - Method used in Query Construction          
      - Term Weighting (weights based on terms in topics)?: Yes. ltc 
      - Phrase Extraction from Topics?: No 
      - Syntactic Parsing of Topics?: No 
      - Word Sense Disambiguation?:  No 
      - Proper Noun Identification Algorithm?: No 
      - Tokenizer?: No                
      - Heuristic Associations to Add Terms?: No 
      - Expansion of Queries using Previously-Constructed Data Structure?: No              
      - Automatic Addition of Boolean Connectors or Proximity Operators?: No 
      - Other: No 

  Searching

    Search Times

      - Run ID: umcpa1 
      - Computer Time to Search (Average per Query, in CPU seconds): 60 
      - Component Times: Compute cosines: 57 , Sort: 3  

    Machine 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?: No  
      - Neural Networks?: No 
      - Conceptual Graph Matching?: No 
      - Other: No  

    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?: 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: No 

    Machine Information

    - Machine Type for TREC Experiment: SPARC 20 
    - Was the Machine Dedicated or Shared: Dedicated 
    - Amount of Hard Disk Storage (in MB): 8 GB 
    - Amount of RAM (in MB):  64 
    - Clock Rate of CPU (in MHz): 75 

    System Comparisons 

    - Amount of "Software Engineering" which went into the Development of the 
System : Very little 
    - Given appropriate resources            
      - Could your system run faster?: Yes 
      - By how much (estimate)?: 50% 
    - Features the System is Missing that would be beneficial: More RAM