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Sparck Jones has carried on this work using measures of association between keywords based on their frequency of co occurrence that is,the frequency with which any two keywords occur together in the same document
...The term information structure for want of better words covers specifically a logical organisation of information,such as document representatives,for the purpose of information retrieval
...The organisation of these files is produced by an automatic classification method
...Evaluation of retrieval systems has proved extremely difficult
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Salton [9],he says:Clearly in practice it is not possible to match each analysed document with each analysed search request because the time consumed by such operation would be excessive
...Measures of association Some classification methods are based on a binary relationship between objects
...Informally speaking,a measure of association increases as the number or proportion of shared attribute states increases
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The process may involve structuring the information in some appropriate way,such as classifying it
...Finally,we come to the output,which is usually a set of citations or document numbers
...IR in perspective This section is not meant to constitute an attempt at an exhaustive and complete account of the historical development of IR
...Since the emphasis in this book is on a particular approach to document representation,I shall restrict myself here to a few remarks about its history
...At this point,it may be convenient to elaborate on the use of keyword
...The use of statistical information about distributions of words in documents was further exploited by Maron and Kuhns [11]who obtained statistical associations between keywords
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where [[rho]]...[[rho]]X,Y W 0 which implies using the expression for the partial correlation that [[rho]]X,Y [[rho]]X,W [[rho]]Y,W Since [[rho]]X,Y <1,[[rho]]X,W <1,[[rho]]Y,W <1 this in turn implies that under the hypothesis of conditional independence [[rho]]X,Y <[[rho]]X,W or [[rho]]Y,W Hence if W is a random variable representing relevance then thecorrelation between it and either index term is greater than the correlation between the index terms
...Qualitatively I shall try and generalise this to functions other than correlation coefficients,Linfott [27]defines a type of informational correlation measure by rij 1 exp 2 I xi,xj [1 2]0 <rij <1 or where I xi,xj is the now familiar expected mutual information measure
...I xi,xj <I xi,W or I xj,W,where I
...Discrimination Gain Hypothesis:Under the hypothesis ofconditional independence the statistical information contained in oneindex term about another is less than the information contained ineither index term about relevance
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the different contributions made to the measure by the different cells
...Discrimination gain hypothesis In the derivation above I have made the assumption of independence or dependence in a straightforward way
...P xi,xj P xi,xj w 1 P w 1 P xi,xi w 2 P w 2 P xi P xj [P xi w 1 P w 1 P xi,w 2 P w 2][P xj w 1 P w 1 P xj,w 2 P w 2]If we assume conditional independence on both w 1 and w 2 then P xi,xj P xi,w 1 P xj,w 1 P w 1 P xi w 2 P xj w 2 P w 2 For unconditional independence as well,we must have P xi,xj P xi P xj This will only happen when P w 1 0 or P w 2 0,or P xi w 1 P xi w 2,or P xj w 1 P xj w 2,or in words,when at least one of the index terms is useless at discriminating relevant from non relevant documents
...Kendall and Stuart [26]define a partial correlation coefficient for any two distributions by |
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In the past there has been much debate about the validity of evaluations based on relevance judgments provided by erring human beings
...Effectiveness and efficiency Much of the research and development in information retrieval is aimed at improving the effectiveness and efficiency of retrieval
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CHAN,F
...CHANG,C
...CHOU,C
...CHOW,C
...CLEVERDON,C
...CLEVERDON,C
...CLEVERDON,C
...CLIFFORD,H
...CLIMENSON,W
...COATES,E
...CODD,E
...COLE,A
...Comparative Systems Laboratory,An Inquiry into Testing of Information Retrieval Systems,3 Vols
...CONOVER,W
...COOPER,M
...COOPER,W
...COOPER,W
...COOPER,W
...COOPER,W
...CORMACK,R
...COX,D
...CROFT,W
...CROFT,W
...CROFT,W
...CROUCH,D
...CUADRA,A
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