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'''Compound -term processing,''' is the name that is used for a category of techniques in [[Informationinformation retrieval|information-retrieval]], applicationsis thatsearch performsresult matching on the basis of [[compound term]]s. Compound terms are built by combining two (or more) simple terms,; for example, "triple" is a single word term, but "triple heart bypass" is a compound term.
Compound -term processing is a new approach to an old problem: how tocan one improve the relevance of search results without missing anything important whilstwhile maintaining ease of use .? ByUsing formingthis compound (i.e. multi-word) terms and placing these in the search engine's index the search can be performed withtechnique, a higher degree of accuracy because the ambiguity inherent in single words is no longer a problem. A search for ''survival rates following a triple heart bypass in elderly people'' will locate documents about this topic even if this precise phrase is not contained in any document. AThis can be performed by a [[concept search]] , usingwhich "Compounditself Termuses Processing"compound-term canprocessing. This will extract the key concepts automatically (in this case "survival rates", "triple heart bypass" and "elderly people") and use these concepts to select the most relevant documents. ▼In August 2003 [[Concept Searching Limited]] introduced the idea of using statistical Compound Term Processing <ref>{{cite journal|url=http://www.conceptsearching.com/Web/UserFiles/File/Concept%20Searching%20Lateral%20Thinking.pdf|title=Lateral Thinking in Information Retrieval|journal=INFORMATION MANAGEMENT AND TECHNOLOGY|volume=36 PART 4}} British Library Direct catalogue entry can be found here:[http://direct.bl.uk/bld/PlaceOrder.do?UIN=138451913&ETOC=RN]</ref> ▼
== Techniques ==
CLAMOUR<ref>[http://www.statistics.gov.uk/methods_quality/clamour/coordination/wp03.asp] National Statistics CLAMOUR project</ref><ref>[http://www.statistics.gov.uk/methods_quality/clamour/downloads/Clamour_march2002_final_reportAO.pdf] CLAMOUR Final Report</ref> is a European collaborative project which aims to find a better way to classify when collecting and disseminating industrial information & statistics. In contrast to the techniques discussed by Concept Searching Limited, CLAMOUR appears to be primarily a linguistic approach, rather than one based on statistical modelling.
▲In August 2003 , [[Concept Searching Limited]] introduced the idea of using statistical Compound Term Processingcompound-term processing.<ref>{{cite journal|url=http://www.conceptsearching.com/Web/UserFiles/File/Concept%20Searching%20Lateral%20Thinking.pdf|title=Lateral Thinking in Information Retrieval|journal= INFORMATIONInformation MANAGEMENTManagement ANDand TECHNOLOGYTechnology|volume=36 PART 4 |access-date=2008-06-20|archive-url=https://web.archive.org/web/20171115145846/https://www.conceptsearching.com/Web/UserFiles/File/Concept%20Searching%20Lateral%20Thinking.pdf|archive-date=2017-11-15|url-status=dead}} The British Library Direct catalogue entry can be found here:[http://direct.bl.uk/bld/PlaceOrder.do?UIN=138451913&ETOC=RN] {{Webarchive|url=https://web.archive.org/web/20120210133832/http://direct.bl.uk/bld/PlaceOrder.do?UIN=138451913&ETOC=RN |date=2012-02-10 }}</ref>
Compound Term Processing is important because it allows search (and other Information Retrieval) applications to perform their matching on the basis of multi-word concepts rather than single words in isolation which can be highly ambiguous. ▼
CLAMOUR is a European collaborative project which aims to find a better way to classify when collecting and disseminating industrial information and statistics. CLAMOUR appears to use a linguistic approach, rather than one based on [[statistical model|statistical modelling]].<ref>[http://webarchive.nationalarchives.gov.uk/20040117000117/statistics.gov.uk/methods_quality/clamour/default.asp] National Statistics CLAMOUR project</ref>
Most [[search engine]]s simply look for documents that contain the words that the user enters into the search box (aka "[[keyword search]]" engines). [[Boolean search]] engines add a degree of sophistication by allowing the user to specify additional requirements but most users struggle to comprehend and use the necessary syntax (e.g. Tiger NEAR Woods AND (golf OR golfing) NOT Volkswagen). [[Phrase search]] is easier to understand but can lead to many useful documents being missed if they do not contain the exact phrase specified. ▼
== History ==
Techniques for probabilistic weighting of single word terms dates back to at least 1976 and the landmark publication by Stephen E. Robertson <ref>http://www.soi.city.ac.uk/~ser/homepage.html Stephen E. Robertson</ref> and [[Karen Spärck Jones]]: Relevance weighting of search terms originally published in the Journal of the American Society for Information Science.<ref>[http://www.soi.city.ac.uk/~ser/papers/RSJ76.pdf] Relevance weighting of search terms</ref> Robertson has stated that the assumption of word independence is not justified and exists simply as a matter of mathematical convenience. The objection to assumptions about term independence are not new, dating back to at least 1964 when H. H. Williams expressed it this way: "The assumption of independence of words in a document is usually made as a matter of mathematical convenience".<ref>WILLIAMS, J.H., 'Results of classifying documents with multiple discriminant functions', In : Statistical Association Methods for Mechanized Documentation, National Bureau of Standards, Washington, 217-224 (1965).</ref> ▼
▲Techniques for probabilistic weighting of single word terms datesdate back to at least 1976 andin the landmark publication by [[Stephen E. Robertson <ref>http://www.soi.city.ac.uk/~ser/homepage.html(computer scientist)|Stephen E. Robertson </ref>]] and [[Karen Spärck Jones]] :.<ref>{{Cite journal | doi = 10.1002/asi.4630270302| title = Relevance weighting of search terms | originallyjournal published in the= Journal of the American Society for Information Science | volume = 27| issue = 3| pages = 129| year = 1976| last1 = Robertson | first1 = S. <ref>[http://www E. soi | authorlink1 = Stephen Robertson (computer scientist)| last2 = Spärck Jones | first2 = K. city.ac.uk/~ser/papers/RSJ76.pdf] Relevance| weightingauthorlink2 of= searchKaren termsSpärck Jones}}</ref> Robertson has stated that the assumption of word independence is not justified and exists simply as a matter of mathematical convenience. TheHis objection to assumptions aboutthe term independence areis not a new idea, dating back to at least 1964 when H. H. Williams expressedstated it this way:that " The[t]he assumption of independence of words in a document is usually made as a matter of mathematical convenience".<ref> {{cite journal |last=WILLIAMS , |first=J.H. , '|title=Results of classifying documents with multiple discriminant functions ', In |url=http: //oai.dtic.mil/oai/oai?verb=getRecord&metadataPrefix=html&identifier=AD0612272 |journal=Statistical Association Methods for Mechanized Documentation, National Bureau of Standards , |___location=Washington , 217-224|pages=217–224 (|year=1965 ) |access-date=2015-05-21 |archive-url=https://web. archive.org/web/20110717145048/http://oai.dtic.mil/oai/oai?verb=getRecord |archive-date=2011-07-17 |url-status=dead }}</ref>
▲Compound term processing is a new approach to an old problem: how to improve the relevance of search results without missing anything important whilst maintaining ease of use. By forming compound (i.e. multi-word) terms and placing these in the search engine's index the search can be performed with a higher degree of accuracy because the ambiguity inherent in single words is no longer a problem. A search for ''survival rates following a triple heart bypass in elderly people'' will locate documents about this topic even if this precise phrase is not contained in any document. A [[concept search]] using "Compound Term Processing" can extract the key concepts automatically (in this case "survival rates", "triple heart bypass" and "elderly people") and use these to select the most relevant documents.
In 2004, Anna Lynn Patterson filed a number of patents on the"phrase-based subjectsearching ofin "Phrasean based indexing andinformation retrieval system" and<ref>{{patent|US|20060031195}}</ref> to which [[Google]] subsequently acquired the rights. A full discussion of the patents can be found here: <ref>[http://www.webmasterwomanseobythesea.com/search-engines2012/phrase02/google-basedacquires-indexing.htmlcuil-patent-applications/ WebmasterGoogle Woman].Acquires Cuil ThePatent patents themselves can be found online, for example:.<ref>[http://appft1.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PG01&p=1&u=%2Fnetahtml%2FPTO%2Fsrchnum.html&r=1&f=G&l=50&s1=%2220060031195%22.PGNR.&OS=DN/20060031195&RS=DN/20060031195Applications] US Patent: 20060031195</ref>
== Adaptability ==
Statistical Compound Term Processing is more adaptive than the "phrase based indexing and retrieval" detailed by Anna Lynn Patterson in her patent applications. The "phrase based indexing" is targeted at searching the World Wide Web where an extensive statistical knowledge of common searches can be used to identify candidate phrases. Statistical Compound Term Processing is more suited to [[Enterprise Search]] applications where such [[A priori and a posteriori|a priori]] knowledge is not available. ▼
▲Statistical Compoundcompound-term Term Processingprocessing is more adaptiveadaptable than the "phraseprocess based indexing and retrieval" detaileddescribed by Anna Lynn Patterson in her patent applications. TheHer "phrase based indexing"process is targeted at searching the [[World Wide Web ]] where an extensive statistical knowledge of common searches can be used to identify candidate phrases. Statistical Compoundcompound Termterm Processingprocessing is more suited to [[ Enterpriseenterprise Searchsearch]] applications where such [[A priori and a posteriori|a priori]] knowledge is not available.
Statistical Compound Term Processing is also more adaptive than the linguistic approach taken by the CLAMOUR project which considers the syntactic properties of the terms (part of speech, gender, number) and their combination. CLAMOUR is highly language dependent, whereas the statistical approach is language independent. ▼
▲Statistical Compoundcompound-term Term Processingprocessing is also more adaptiveadaptable than the linguistic approach taken by the CLAMOUR project , which considersmust consider the syntactic properties of the terms ( i.e. part of speech, gender, number , etc.) and their combinationcombinations. CLAMOUR is highly language -dependent, whereas the statistical approach is language -independent.
== Applications ==
▲Compound -term Termprocessing Processingallows isinformation-retrieval importantapplications, becausesuch it allowsas [[search (and other Information Retrieval) applicationsengines]], to perform their matching on the basis of multi-word concepts , rather than on single words in isolation which can be highly ambiguous.
▲MostEarly [[search engine]]sengines simply looklooked for documents that containcontaining the words thatentered by the user enters into the search box (aka. These are known as "[[keyword search]] " engines ). [[Boolean search]] engines add a degree of sophistication by allowing the user to specify additional requirements . butFor most users struggle to comprehend and use the necessary syntax (e.g.example, "Tiger NEAR Woods AND (golf OR golfing) NOT Volkswagen )." [[Phraseuses search]]the isoperators easier"NEAR", "AND", "OR" and "NOT" to understandspecify butthat canthese leadwords tomust manyfollow usefulcertain documentsrequirements. beingA missed[[phrase ifsearch]] theyis dosimpler notto containuse, but requires that the exact phrase specified appear in the results.
==See also==
* [http://www.conceptsearching.com/ [[Concept Searching Limited ]] ▼* [[Enterprise search]]
* [[Information retrieval]]
== References ==
{{Reflist|30em}}
== External links ==
▲*[http://www.conceptsearching.com/ Concept Searching Limited]
*[http://www.webmasterwoman.com/search-engines/phrase-based-indexing.html Webmaster Woman]
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{{Natural Language Processing}}
{{DEFAULTSORT:Compound Term Processing}}
[[Category:Information retrieval techniques]]
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