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Simple, Proven Approaches To Text Retrieval

Simple, Proven Approaches To Text Retrieval. S. E. Robertson & K.Sparck Jones. Presenters: Tuncer Turhan Yakup Korkmaz Ömer Köksal. Term matching / weighting. Terms and matching Sources for term weighting Collection frequency n = the number of documents term t(i) occurs in

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Simple, Proven Approaches To Text Retrieval

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  1. Simple, Proven Approaches To Text Retrieval S. E. Robertson & K.Sparck Jones Presenters: Tuncer Turhan Yakup Korkmaz Ömer Köksal

  2. Term matching / weighting • Terms and matching • Sources for term weighting • Collectionfrequency n = the number of documents term t(i) occurs in N = the number of documents in the collection CFW (i) = log N - log n • Termfrequency TF (i,j) = the number of occurrences of term t(i) in document d(j)

  3. Term matching / weighting • Sources for term weighting (Continued) • Documentlength DL (j) = the total of term occurrences in document d(j) NDL (j) = (DL (j)) / (Average DL for all documents) • Combiningtheevidence CW (i,j) = [ CFW (i) * TF (i,j) * (K1+1) ] / [ K1 * ( (1-b) + (b * (NDL (j)) ) ) + TF (i,j) ] K1 and b are tuning constants.

  4. Iterative searching • Relevanceweights r = the number of known relevant documents term t(i) occurs in R = the number of known relevant document for a request RW (i) = log [ ( (r+0.5)(N-n-R+r+0.5) ) / ( (n-r+0.5)(R-r+0.5) ) ] • Queryexpansion OW (i) = r * RW (i)

  5. Iterative searching • Iterative combination CIW (i,j) = [ RW (i) * TF (i,j) * (K1+1) ] / [ K1 * ( (1-b) + (b * (NDL (j)) ) ) + TF (i,j) ]

  6. Details - Elaborations • Firstrequests • Longerqueries QACW (i) = QF(i) * CW(i,j) QACIW (i) = QF(i) * CIW(i,j) • Elaborations

  7. Thank you for listening…

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