1977. G. Salton and H. J. Schneider, pp. 251-62. efficient clustering techniques [Author Willett] 14.8.4 Use of Ranking in Two-level Search Schemes Using Harman's normalized frequency as an example, the raw frequency for each term from the final table of the inversion process would be transformed into a log function and then divided by the log of the length of the corresponding record (the lengths of the records were collected and saved in the parsing step). The dictionary and postings file shown (Figure 14.3) stores a term-weight of simply the raw frequency of a term in a record. 1980. Paper presented at the Sixth International Conference on Research and Development in Information Retrieval, Bethesda, Maryland. 1984. 1989), which is based on a two-stage search using signature files for a first cut and then ranking retrieved documents by term-weighting. The term-weighting is done in the search process using the raw frequencies stored in the postings lists. A possible alternative is the noise or entropy measure tried in several experiments . 14.7.1 Handling Both Stemmed and Unstemmed Query Terms 1983. MARON, M. E., and J. L. KUHNS. New York: Elsevier Science Publishers. A second reason for the inconsistent improvements found for within-document frequencies is the fact that some collections have very short documents (such as titles only) and therefore within-document frequencies play no role in these collections. The only methodology for this that has received widespread testing using the standard collections is the P-Norm method allowing the use of soft Boolean operators. 14.6.2 Searching the Inverted File HARMAN, D., and G. CANDELA. For further details, see Chapter 11. There are several major inefficiencies of this technique. Instead it is a bucketed (10 slots/bucket) hash table that is accessed by hashing the query terms to find matching entries. If the query term is not common, it is then passed through the stemming routine and a binary search for that stem is executed against the dictionary. K = a constant for adjusting the relative importance of the two The following method serves only as an illustration of a very simple pruning procedure, with an example of the time savings that can be expected using a pruning technique on a large data set. 14.8 TOPICS RELATED TO RANKING The description of the search process does not include the interface issues or the actual data retrieval issues. Croft and Savino (1988) provide a ranking technique that combines the IDF measure with an estimated normalized within-document frequency, using simple modifications of the standard signature file technique (see the chapter on signature files). Using Harman's normalized frequency as an example, the raw frequency for each term from the final table of the inversion process would be transformed into a log function and then divided by the log of the length of the corresponding record (the lengths of the records were collected and saved in the parsing step). This method is based on the fact that most records for queries are retrieved based on matching only query terms of high data set frequency. 117-51. This method was used in the prototype built by Harman and Candela (1990) and provided a very effective way of handling phrases and other limitations without increasing indexing overhead. HARPER, D. J. "Testing of a Natural Language Retrieval System for a Full Text Knowledge Base." "On the Specification of Term Values in Automatic Indexing." 1. BOOKSTEIN, A. Paper presented at the Statistical Association Methods for Mechanized Documentation. Their ranking algorithms used not only weights based on term importance both within an entire collection and within a given document, but also on the structural position of the term, such as within summary paragraphs versus within text paragraphs. CROFT, W. B., and P. SAVINO. The algorithm assumes that relative rankings are absolute/static, like if A < B and C < A, there's no reason to compare B and C. per query (no pruning) J. American Society for Information Science, 27(3), 129-46. That study also suggests that the ability of a ranking system to use the smaller inverted files discussed in this chapter makes storage and efficiency of ranking techniques competitive with that of signature files. 1989. 1960. Many combinations of term-weighting can be done using the inner product. "A Document Retrieval System Based on Nearest Neighbor Searching." User weighting can also be considered as additional weighting, although this type of weighting has generally proven unsatisfactory in the past. the queries would be parsed into single terms and the documents ranked as if there were no special syntax. "SIBRIS: the Sandwich Interactive Browsing and Ranking Information System." The system accepts queries that are either Boolean logic strings (similar to many commercial on-line systems) or natural language queries (processed as Boolean queries with implicit OR connectors between all query terms). SPARCK JONES, K. 1979a. Englewood Cliffs, N.J.: Prentice Hall. 1979. 14.7.2 Searching in Very Large Data Sets IBM J. J. of Information Science, 6, 25-33. CROFT, W. B. 1974. N = the number of documents in the collection 1977. The SIRE system, as implemented at Syracuse University (Noreault et al. It can be very useful to add additional weight for document structure, such as higher weightings for terms appearing in the title or abstract versus those appearing only in the text. The list of ranked documents is returned as before, but only documents passing the added restriction are given to the user. Improving Subject Retrieval in Online Catalogues, British Library Research Paper 24. SALTON, G., and C. S. YANG. "On the Specification of Term Values in Automatic Indexing." The response time for the 806 megabyte data set assumes parallel processing of the three parts of the data set, and would be longer if the data set could not be processed in parallel. terms per query The use of the fixed block of storage to accumulate record weights that is described in the basic search process (section 14.6) becomes impossible for this huge data set. VAN RIJSBERGEN, C. J. An example of the merged inverted file is shown in Figure 14.5. Figure 14.5: Merged dictionary and postings file The use of ranking means that there is little need for the adjacency operations or field restrictions necessary in Boolean. Information Science, 6, 59-66. This would require a different organization of the final inverted index file that contains the dictionary, but would not affect the postings lists (which would be sequentially stored for search time improvements). Croft and Savino (1988) provide a ranking technique that combines the IDF measure with an estimated normalized within-document frequency, using simple modifications of the standard signature file technique (see the chapter on signature files). "Experiments with Representation in a Document Retrieval System." "Operations Research Applied to Document Indexing and Retrieval Decisions." The penalty paid for this efficiency is the need to update the index as the data set changes. 1989), which is based on a two-stage search using signature files for a first cut and then ranking retrieved documents by term-weighting. Information Processing and Management, 15(3), 133-44. 3. It was also suggested that clustering could improve the performance of retrieval by pregrouping like documents (Jardine and van Rijsbergen 1971). LUHN, H. P. 1957. 1984. HARTER, S. P. 1975. 1984. BERNSTEIN, L. M., and R. E. WILLIAMSON. For smaller data sets, or for environments where ease of update and flexibility are more important than query response time, the inverted file could have a structure more conducive to updating. "Testing of a Natural Language Retrieval System for a Full Text Knowledge Base." 3. J. The combination of the within-document frequency with the IDF weight often provides even more improvement. Association for Computing Machinery, 23(1), 76-88. The major modification to the basic search process is to correctly merge postings from the query terms based on the Boolean logic in the query before ranking is done. 1979. A Boolean query is processed in two steps. "From Research to Application: The CITE Natural Language Information Retrieval System," in Research and Development in Information Retrieval, eds. This system therefore is much more flexible and much easier to update than the basic inverted file and search process described in section 14.6. An example of the merged inverted file is shown in Figure 14.5. SPARCK JONES, K. 1979b. LUHN, H. P. 1957. It should be noted that, unlike section 14.6, some of the implementations discussed here should be used with caution as they are usually more experimental, and may have unknown problems or side effects. Report from the School of Information Studies, Syracuse University, Syracuse, New York. J. The basic inverted file creation and search process described in section 14.6 assumes a fairly static data set or a willingness to do frequent updates to the entire inverted file. ACM Transactions on Office Information Systems, 6(1), 42-62. If the IDF is greater than or equal to one third the maximum IDF of any term in the data set, then repeat steps 2, 3, and 4. A second reason for the inconsistent improvements found for within-document frequencies is the fact that some collections have very short documents (such as titles only) and therefore within-document frequencies play no role in these collections. "Search Term Relevance Weighting Given Little Relevance Information." "Comparing and Combining the Effectiveness of Latent Semantic Indexing and the Ordinary Vector Space Model for Information Retrieval." "A Probabilistic Approach to Automatic Keyword Indexing." maxfreqj = the maximum frequency of any term in document j 2. Ranking retrieval systems and relevance feedback have been closely connected throughout the past 25 years of research. The basic ranking search methodology described in the chapter is so fast that it is effective to use in situations requiring simple restrictions on natural language queries. SALTON, G. 1971. J. J. American Society for Information Science, 35(4), 235-47. Association for Computing Machinery, 7(3), 216-44. This additional weighting needs to be considered with respect to the particular data set being used for searching. The basic search process is therefore unchanged except that instead of each record of the data set having a unique accumulator, the accumulators hold only a subset of the records and each subset is processed as if it were the entire data set, with each set of results shown to the user. This method was used in the prototype built by Harman and Candela (1990) and provided a very effective way of handling phrases and other limitations without increasing indexing overhead. Englewood Cliffs, N.J.: Prentice Hall. DENNIS, S. F. 1964. 109-45. 1990. One alternative ranking using the inner product (but without adjustable constants) is given below. "Foundations of Probabilistic and Utility-Theoretic Indexing." Each query term that is stemmed must now map to multiple dictionary entries, and postings lists must be handled more carefully as some terms have three elements in their postings list and some have only two. 14.6.2 Searching the Inverted File Paper presented at the Sixth International Conference on Research and Development in Information Retrieval, Bethesda, Maryland. SPARCK JONES, K. 1972. In 1982, MEDLINE had approximately 600,000 on-line records, with records being added at a rate of approximately 21,000 per month (Doszkocs 1982). An efficient file structure is used to record which query term appears in which given retrieved document. The same procedure could be done for Croft's normalized frequency or any other normalized frequency used in an inner product similarity function, assuming appropriate record statistics have been stored during parsing. "Optimizations for Dynamic Inverted Index Maintenance." Check the IDF of the next query term. Signature files have also been used in SIBRIS, an operational information retrieval system (Wade et al. A document can then be represented by a vector (t1, t2, t3, . 1990. Then I apply a sum combine on the output. "On the Specification of Term Values in Automatic Indexing." Note that records containing only high-frequency terms will not have any weight added to their accumulator and therefore are not sorted. FRAKES, W. B. NOREAULT, T., M. KOLL, and M. MCGILL. In some cases, however, a stem is produced that leads to improper results, causing query failure. -------------------------------------------------------- TFreqi = the total frequency of term i in the collection CLEVERDON, C. 1983. G. Salton and H. J. Schneider, pp. "On Relevance, Probabilistic Indexing and Information Retrieval." If the stem is found in the dictionary, the address of the postings list for that stem is returned, along with the corresponding IDF and the number of postings. J. American Society for Information Science, 26(5), 280-89. The response time for the 806 megabyte data set assumes parallel processing of the three parts of the data set, and would be longer if the data set could not be processed in parallel. There are several major inefficiencies of this technique. where 14.7.3 A Boolean System with Ranking The search time for this method is heavily dependent on the number of retrieved records and becomes prohibitive when used on large data sets. The Art of Computer Programming, Reading, Mass. VAN RIJSBERGEN. This method was used in the prototype built by Harman and Candela (1990) and provided a very effective way of handling phrases and other limitations without increasing indexing overhead. A second major set of experiments was done by Salton and Yang (1973) to further develop the term-weighting schemes. SPARCK JONES, K. 1973. Association for Computing Machinery, 15(1), 8-36. 1974. A final major bottleneck can be the sort step of the "accumulators" for large data sets. Documentation, 35(4), 285-95. 1. CLEVERDON, C. 1983. It is assumed that a natural language query is passed to the search process in some manner, and that the list of ranked record id numbers that is returned by the search process is used as input to some routine which maps these ids onto data locations and displays a list of titles or short data descriptors for user selection. Although this seems a tedious method of handling phrases or field restrictions, it can be done in parallel with user browsing operations so that users are often unaware that a second processing step is occurring. As can be expected, the search process needs major modifications to handle these hybrid inverted files. Average number of 4.1 3.5 3.5 3.5 Early efforts to improve the efficiency of ranking systems for use in large data sets proposed the use of clustering techniques to avoid dealing with ranking the entire collection (Salton 1971). RAGHAVAN, V. V., H. P. SHI, and C. T. YU. "Automatic Ranked Output from Boolean Searches in SIRE." Note that the use of noise here refers to how much a term can be considered useful for retrieval versus being simply a "noisy" term, and examines the concentration of terms within documents rather than just the number of postings or occurrences. ACM Transactions on Office Information Systems, 6(1), 42-62. "Precision Weighting -- An Effective Automatic Indexing Method." where Her results showed that using the term frequency (or postings) within a collection always improved performance, but that using term frequency (or postings) within a document improved performance only for some collections. Relevance Feedback in Document Retrieval Systems: An Evaluation of Probabilistic Strategies. This section will describe a simple but complete implementation of the ranking part of a retrieval system. This method eliminates the often-wrong Boolean syntax used by end-users, and provides some results even if a query term is incorrect, that is, it is not the term used in the data, it is misspelled, and so on. 14.7 MODIFICATIONS AND ENHANCEMENTS TO THE BASIC INDEXING AND SEARCH PROCESSES (pruning) J. American Society for Information Science, 25, 312-19. "A Document Retrieval System Based on Nearest Neighbor Searching." Information Processing and Management, 25(4), 347-61. 3. 1979. Robertson and Sparck Jones used these four formulas in a series of experiments with the manually indexed Cranfield collection. G. Salton and H. J. Schneider, pp. A possible alternative is the noise or entropy measure tried in several experiments . LUHN, H. P. 1957. SALTON, G. 1971. This usually requires a second pass over the actual document, that is each document marked as containing "nearest" and "neighbor" is passed through a fast string search algorithm looking for the phrase "nearest neighbor," or all documents containing "Willett" have their author field checked for "Willett." The user may request ranked output. G. Salton and H. J. Schneider, pp. The Art of Computer Programming, Reading, Mass. 1984. YU, C. T., and G. SALTON. The list of ranked documents is returned as before, but only documents passing the added restriction are given to the user. This necessity for ease of update also changes the postings structure, which becomes a series of linked variable length lists capable of infinite update expansion. 2. freqij = the frequency of term i in document j A check needs to be made after step 1 for this. 1988. Signature files have also been used in SIBRIS, an operational information retrieval system (Wade et al. J. 14.8.4 Use of Ranking in Two-level Search Schemes "The Measurement of Term Importance in Automatic Indexing." Clearly, for data sets that are relatively small it is best to use the two separate inverted files because the storage savings are not large enough to justify the additional complexity in indexing and searching. BURKOWSKI, F. J. Ranking models can be divided into two types: those that rank the query against individual documents and those that rank the query against entire sets of related documents. There have been several studies examining the various factors involved in ranking that have not been based on any particular model but have instead used some method of comparing directly various similarity measures and term-weighting schemes. 1974. Association for Computing Machinery, 23(1), 76-88. CROFT, W. B., and P. SAVINO. This necessity for ease of update also changes the postings structure, which becomes a series of linked variable length lists capable of infinite update expansion. BELKIN, N. J. and W. B. CROFT. SPARCK JONES, K. 1979a. 1985. 1981. "The Implementation of a Document Retrieval System," in Research and Development in Information Retrieval, eds. McGill et al. The input query is processed similarly to a natural language query, except that the system notes the presence of special syntax denoting phrase limits or other field or proximity limitations. If option 3 was used for weighting, then this total is immediately available and only a simple addition is needed. Information Technology: Research and Development, 2(1), 1-21. "Retrieval Techniques," in Williams, M. 14.8 TOPICS RELATED TO RANKING Using the following examples One way of using an inverted file to produce statistically ranked output is to first retrieve all records containing the search terms, then use the weighting information for each term in those records to compute the total weight for each of those retrieved records, and finally sort those records. Suppose you have a decision to make it one of Figure 14.1 shows some timing results this! Program to allow easier updating is given below needs major modifications to handle these inverted. Of this pruning algorithm frequency weighting improved performance over no term-weighting ( in varying amounts depending search. Subsetting or segmenting is done in Croft 's experimental re trieval system Croft... With pruning is as follows: 1 were extracted from 3-axis acceleration and angular velocity signals by. 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