Search (17 results, page 1 of 1)

  • × author_ss:"Robertson, S.E."
  1. MacFarlane, A.; Robertson, S.E.; McCann, J.A.: Parallel computing for passage retrieval (2004) 0.03
    0.032256197 = product of:
      0.048384294 = sum of:
        0.021338228 = weight(_text_:on in 5108) [ClassicSimilarity], result of:
          0.021338228 = score(doc=5108,freq=2.0), product of:
            0.109763056 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.04990557 = queryNorm
            0.19440265 = fieldWeight in 5108, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.0625 = fieldNorm(doc=5108)
        0.027046064 = product of:
          0.054092128 = sum of:
            0.054092128 = weight(_text_:22 in 5108) [ClassicSimilarity], result of:
              0.054092128 = score(doc=5108,freq=2.0), product of:
                0.1747608 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.04990557 = queryNorm
                0.30952093 = fieldWeight in 5108, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.0625 = fieldNorm(doc=5108)
          0.5 = coord(1/2)
      0.6666667 = coord(2/3)
    
    Abstract
    In this paper methods for both speeding up passage processing and examining more passages using parallel computers are explored. The number of passages processed are varied in order to examine the effect on retrieval effectiveness and efficiency. The particular algorithm applied has previously been used to good effect in Okapi experiments at TREC. This algorithm and the mechanism for applying parallel computing to speed up processing are described.
    Date
    20. 1.2007 18:30:22
  2. Robertson, S.E.; Hancock-Beaulieu, M.M.: On the evaluation of IR systems (1992) 0.01
    0.014225486 = product of:
      0.042676456 = sum of:
        0.042676456 = weight(_text_:on in 2619) [ClassicSimilarity], result of:
          0.042676456 = score(doc=2619,freq=2.0), product of:
            0.109763056 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.04990557 = queryNorm
            0.3888053 = fieldWeight in 2619, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.125 = fieldNorm(doc=2619)
      0.33333334 = coord(1/3)
    
  3. Robertson, S.E.: OKAPI at TREC-1 (1994) 0.01
    0.012573673 = product of:
      0.03772102 = sum of:
        0.03772102 = weight(_text_:on in 7953) [ClassicSimilarity], result of:
          0.03772102 = score(doc=7953,freq=4.0), product of:
            0.109763056 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.04990557 = queryNorm
            0.3436586 = fieldWeight in 7953, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.078125 = fieldNorm(doc=7953)
      0.33333334 = coord(1/3)
    
    Abstract
    Describes the work carried out on the TREC-2 project following the results of the TREC-1 project. Experiments were conducted on the OKAPI experimental text information retrieval system which investigated a number of alternative probabilistic term weighting functions in place of the 'standard' Robertson Sparck Jones weighting functions used in TREC-1
  4. Bovey, J.D.; Robertson, S.E.: ¬An algorithm for weighted searching on a Boolean system (1984) 0.01
    0.0124473 = product of:
      0.0373419 = sum of:
        0.0373419 = weight(_text_:on in 788) [ClassicSimilarity], result of:
          0.0373419 = score(doc=788,freq=2.0), product of:
            0.109763056 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.04990557 = queryNorm
            0.34020463 = fieldWeight in 788, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.109375 = fieldNorm(doc=788)
      0.33333334 = coord(1/3)
    
  5. Robertson, S.E.; Walker, S.; Hancock-Beaulieu, M.M.: Large test collection experiments of an operational, interactive system : OKAPI at TREC (1995) 0.01
    0.010779679 = product of:
      0.032339036 = sum of:
        0.032339036 = weight(_text_:on in 6964) [ClassicSimilarity], result of:
          0.032339036 = score(doc=6964,freq=6.0), product of:
            0.109763056 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.04990557 = queryNorm
            0.29462588 = fieldWeight in 6964, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.0546875 = fieldNorm(doc=6964)
      0.33333334 = coord(1/3)
    
    Abstract
    The Okapi system has been used in a series of experiments on the TREC collections, investiganting probabilistic methods, relevance feedback, and query expansion, and interaction issues. Some new probabilistic models have been developed, resulting in simple weigthing functions that take account of document length and within document and within query term frequency. All have been shown to be beneficial when based on large quantities of relevance data as in the routing task. Interaction issues are much more difficult to evaluate in the TREC framework, and no benefits have yet been demonstrated from feedback based on small numbers of 'relevant' items identified by intermediary searchers
  6. Robertson, S.E.: Some recent theories and models in information retrieval (1980) 0.01
    0.010669115 = product of:
      0.032007344 = sum of:
        0.032007344 = weight(_text_:on in 1326) [ClassicSimilarity], result of:
          0.032007344 = score(doc=1326,freq=2.0), product of:
            0.109763056 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.04990557 = queryNorm
            0.29160398 = fieldWeight in 1326, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.09375 = fieldNorm(doc=1326)
      0.33333334 = coord(1/3)
    
    Source
    Theory and application of information research. Proc. of the 2nd Int. Research Forum on Information Science, 3.-6.8.1977, Copenhagen. Ed.: O. Harbo u. L. Kajberg
  7. Robertson, S.E.; Beaulieu, M.: Research and evaluation in information retrieval (1997) 0.01
    0.010058938 = product of:
      0.030176813 = sum of:
        0.030176813 = weight(_text_:on in 7445) [ClassicSimilarity], result of:
          0.030176813 = score(doc=7445,freq=4.0), product of:
            0.109763056 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.04990557 = queryNorm
            0.27492687 = fieldWeight in 7445, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.0625 = fieldNorm(doc=7445)
      0.33333334 = coord(1/3)
    
    Abstract
    Offered as a discussion document drawing on the experiences of the Okapi team in developing information retrieval systems. Raises some of the issues currently exercising the information retrieval community in the context of experimentation and evaluation
    Footnote
    Contribution to a thematic issue on Okapi and information retrieval research
  8. Vechtomova, O.; Karamuftuoglum, M.; Robertson, S.E.: On document relevance and lexical cohesion between query terms (2006) 0.01
    0.009239726 = product of:
      0.027719175 = sum of:
        0.027719175 = weight(_text_:on in 987) [ClassicSimilarity], result of:
          0.027719175 = score(doc=987,freq=6.0), product of:
            0.109763056 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.04990557 = queryNorm
            0.25253648 = fieldWeight in 987, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.046875 = fieldNorm(doc=987)
      0.33333334 = coord(1/3)
    
    Abstract
    Lexical cohesion is a property of text, achieved through lexical-semantic relations between words in text. Most information retrieval systems make use of lexical relations in text only to a limited extent. In this paper we empirically investigate whether the degree of lexical cohesion between the contexts of query terms' occurrences in a document is related to its relevance to the query. Lexical cohesion between distinct query terms in a document is estimated on the basis of the lexical-semantic relations (repetition, synonymy, hyponymy and sibling) that exist between there collocates - words that co-occur with them in the same windows of text. Experiments suggest significant differences between the lexical cohesion in relevant and non-relevant document sets exist. A document ranking method based on lexical cohesion shows some performance improvements.
  9. Robertson, S.E.: On relevance weight estimation and query expansion (1986) 0.01
    0.008890929 = product of:
      0.026672786 = sum of:
        0.026672786 = weight(_text_:on in 3875) [ClassicSimilarity], result of:
          0.026672786 = score(doc=3875,freq=2.0), product of:
            0.109763056 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.04990557 = queryNorm
            0.24300331 = fieldWeight in 3875, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.078125 = fieldNorm(doc=3875)
      0.33333334 = coord(1/3)
    
  10. Robertson, S.E.; Walker, S.; Beaulieu, M.: Laboratory experiments with Okapi : participation in the TREC programme (1997) 0.01
    0.008801571 = product of:
      0.026404712 = sum of:
        0.026404712 = weight(_text_:on in 2216) [ClassicSimilarity], result of:
          0.026404712 = score(doc=2216,freq=4.0), product of:
            0.109763056 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.04990557 = queryNorm
            0.24056101 = fieldWeight in 2216, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.0546875 = fieldNorm(doc=2216)
      0.33333334 = coord(1/3)
    
    Abstract
    Briefly reviews the history of laboratory testing of information retrieval systems, focusing on the idea of a general purpose test collection of documents, queries and relevance judgements. Gives an overview of the methods used in TREC (Text Retrieval Conference) which is concerned with an ideal test collection, and discusses the Okapi team's participation in TREC. Also discusses some of the issues surrounding the difficult problem of interactive evaluation in TREC. The reconciliation of the requirements of the laboratory context with the concerns of interactive retrieval has a long way to go
    Footnote
    Contribution to a thematic issue on Okapi and information retrieval research
  11. Huang, X.; Robertson, S.E.: Application of probilistic methods to Chinese text retrieval (1997) 0.01
    0.008801571 = product of:
      0.026404712 = sum of:
        0.026404712 = weight(_text_:on in 4706) [ClassicSimilarity], result of:
          0.026404712 = score(doc=4706,freq=4.0), product of:
            0.109763056 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.04990557 = queryNorm
            0.24056101 = fieldWeight in 4706, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.0546875 = fieldNorm(doc=4706)
      0.33333334 = coord(1/3)
    
    Abstract
    Discusses the use of text retrieval methods based on the probabilistic model with Chinese language material. Since Chinese text has no natural word boundaries, either a dictionary based word segmentation method must be applied to the text, or indexing and searching must be done in terms of single Chinese characters. In either case, it becomes important to have a good way of dealing with phrases or contoguous strings of characters; the probabilistic model does not at present have such a facility. Proposes some ad hoc modifications of the probabilistic weighting function and matching method for this purpose
    Footnote
    Contribution to a thematic issue on Okapi and information retrieval research
  12. Robertson, S.E.: On term selection for query expansion (1990) 0.01
    0.007112743 = product of:
      0.021338228 = sum of:
        0.021338228 = weight(_text_:on in 2650) [ClassicSimilarity], result of:
          0.021338228 = score(doc=2650,freq=2.0), product of:
            0.109763056 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.04990557 = queryNorm
            0.19440265 = fieldWeight in 2650, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.0625 = fieldNorm(doc=2650)
      0.33333334 = coord(1/3)
    
  13. Robertson, S.E.: Overview of the Okapi projects (1997) 0.01
    0.007112743 = product of:
      0.021338228 = sum of:
        0.021338228 = weight(_text_:on in 4703) [ClassicSimilarity], result of:
          0.021338228 = score(doc=4703,freq=2.0), product of:
            0.109763056 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.04990557 = queryNorm
            0.19440265 = fieldWeight in 4703, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.0625 = fieldNorm(doc=4703)
      0.33333334 = coord(1/3)
    
    Footnote
    Contribution to a thematic issue on Okapi and information retrieval research
  14. Robertson, S.E.: ¬The parametric description of retrieval tests : Part I: The basic parameters (1969) 0.01
    0.00622365 = product of:
      0.01867095 = sum of:
        0.01867095 = weight(_text_:on in 4155) [ClassicSimilarity], result of:
          0.01867095 = score(doc=4155,freq=2.0), product of:
            0.109763056 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.04990557 = queryNorm
            0.17010231 = fieldWeight in 4155, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.0546875 = fieldNorm(doc=4155)
      0.33333334 = coord(1/3)
    
    Abstract
    Some parameters and techniques in use for describing the results of test on IR system are analysed. Several considerations outside the scope of the usual 2X2 table are relevant to the choice of parameters. In particular, a variable which produces a 'performance curve' of a system corresponds to an extension of the 2x2 table. Also, the statistical relationships between parameters are all-important. It is considered that precision is not such a useful measure of performance (in conjunction with recall)as fallout. A more powerful alternative to Cleverdon's 'invitable inverse relationship between recall and precision'is proposed and justified, namely that the recall-fallout graph is convex.
  15. MacFarlane, A.; McCann, J.A.; Robertson, S.E.: Parallel methods for the generation of partitioned inverted files (2005) 0.01
    0.0053345575 = product of:
      0.016003672 = sum of:
        0.016003672 = weight(_text_:on in 651) [ClassicSimilarity], result of:
          0.016003672 = score(doc=651,freq=2.0), product of:
            0.109763056 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.04990557 = queryNorm
            0.14580199 = fieldWeight in 651, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.046875 = fieldNorm(doc=651)
      0.33333334 = coord(1/3)
    
    Abstract
    Purpose - The generation of inverted indexes is one of the most computationally intensive activities for information retrieval systems: indexing large multi-gigabyte text databases can take many hours or even days to complete. We examine the generation of partitioned inverted files in order to speed up the process of indexing. Two types of index partitions are investigated: TermId and DocId. Design/methodology/approach - We use standard measures used in parallel computing such as speedup and efficiency to examine the computing results and also the space costs of our trial indexing experiments. Findings - The results from runs on both partitioning methods are compared and contrasted, concluding that DocId is the more efficient method. Practical implications - The practical implications are that the DocId partitioning method would in most circumstances be used for distributing inverted file data in a parallel computer, particularly if indexing speed is the primary consideration. Originality/value - The paper is of value to database administrators who manage large-scale text collections, and who need to use parallel computing to implement their text retrieval services.
  16. Vechtomova, O.; Robertson, S.E.: ¬A domain-independent approach to finding related entities (2012) 0.01
    0.0053345575 = product of:
      0.016003672 = sum of:
        0.016003672 = weight(_text_:on in 2733) [ClassicSimilarity], result of:
          0.016003672 = score(doc=2733,freq=2.0), product of:
            0.109763056 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.04990557 = queryNorm
            0.14580199 = fieldWeight in 2733, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.046875 = fieldNorm(doc=2733)
      0.33333334 = coord(1/3)
    
    Abstract
    We propose an approach to the retrieval of entities that have a specific relationship with the entity given in a query. Our research goal is to investigate whether related entity finding problem can be addressed by combining a measure of relatedness of candidate answer entities to the query, and likelihood that the candidate answer entity belongs to the target entity category specified in the query. An initial list of candidate entities, extracted from top ranked documents retrieved for the query, is refined using a number of statistical and linguistic methods. The proposed method extracts the category of the target entity from the query, identifies instances of this category as seed entities, and computes similarity between candidate and seed entities. The evaluation was conducted on the Related Entity Finding task of the Entity Track of TREC 2010, as well as the QA list questions from TREC 2005 and 2006. Evaluation results demonstrate that the proposed methods are effective in finding related entities.
  17. MacFarlane, A.; McCann, J.A.; Robertson, S.E.: Parallel methods for the update of partitioned inverted files (2007) 0.00
    0.0044454644 = product of:
      0.013336393 = sum of:
        0.013336393 = weight(_text_:on in 819) [ClassicSimilarity], result of:
          0.013336393 = score(doc=819,freq=2.0), product of:
            0.109763056 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.04990557 = queryNorm
            0.121501654 = fieldWeight in 819, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.0390625 = fieldNorm(doc=819)
      0.33333334 = coord(1/3)
    
    Abstract
    Purpose - An issue that tends to be ignored in information retrieval is the issue of updating inverted files. This is largely because inverted files were devised to provide fast query service, and much work has been done with the emphasis strongly on queries. This paper aims to study the effect of using parallel methods for the update of inverted files in order to reduce costs, by looking at two types of partitioning for inverted files: document identifier and term identifier. Design/methodology/approach - Raw update service and update with query service are studied with these partitioning schemes using an incremental update strategy. The paper uses standard measures used in parallel computing such as speedup to examine the computing results and also the costs of reorganising indexes while servicing transactions. Findings - Empirical results show that for both transaction processing and index reorganisation the document identifier method is superior. However, there is evidence that the term identifier partitioning method could be useful in a concurrent transaction processing context. Practical implications - There is an increasing need to service updates, which is now becoming a requirement of inverted files (for dynamic collections such as the web), demonstrating that a shift in requirements of inverted file maintenance is needed from the past. Originality/value - The paper is of value to database administrators who manage large-scale and dynamic text collections, and who need to use parallel computing to implement their text retrieval services.