'''Compound -term processing ,''' refers to a category of techniques used in [[information retrieval|information-retrieval]] , applicationsis thatsearch performresult 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. ▼{{copy edit|for=Use of references (both inline, and ref tags)|date=February 2015}}
Compound -term processing is a new approach to an old problem: how can one improve the relevance of search results while maintaining ease of use? Using this technique, 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. This can be performed by a [[concept search]], which itself uses compound -term processing. 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. ▼▲'''Compound term processing''' refers to a category of techniques used in [[information retrieval]] applications that perform 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.
== Techniques ==
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}} The British Library Direct catalogue entry can be found here:[http://direct.bl.uk/bld/PlaceOrder.do?UIN=138451913&ETOC=RN]</ref> ▼
▲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>
CLAMOUR<ref>[http://webarchive.nationalarchives.gov.uk/20040117000117/statistics.gov.uk/methods_quality/clamour/default.asp] National Statistics CLAMOUR project</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 use a linguistic approach, rather than one based on statistical modelling.
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>
Compound Term Processing allows information retrieval applications, such as search engines, to perform their matching on the basis of multi-word concepts, rather than on single words in isolation which can be highly ambiguous. ▼
== History ==
Most [[search engine]]s simply look for documents containing the words entered by the user into the search box . These are known as [[keyword search]] engines. [[Boolean search]] engines add a degree of sophistication by allowing the user to specify additional requirements. For example, "Tiger NEAR Woods AND (golf OR golfing) NOT Volkswagen" uses the operators "NEAR", "AND", "OR" and "NOT" to specify that these words must follow certain requirements. A [[Phrase search]] is simpler to use, but requires that the exact phrase specified appear in the results. ▼
Techniques for probabilistic weighting of single word terms date back to at least 1976 in the landmark publication by [[Stephen Robertson (computer scientist)|Stephen E. Robertson]] and [[Karen Spärck Jones]].<ref>{{Cite entitledjournal | doi = 10.1002/asi.4630270302| title = "Relevance weighting of search terms",| originallyjournal published in the= ''Journal of the American Society for Information Science''.<ref>{{cite| doivolume = 27| 10issue = 3| pages = 129| year = 1976| last1 = Robertson | first1 = S.1002/asi E.4630270302 | authorlink1 = Stephen Robertson (computer scientist)| last2 = Spärck Jones | first2 = K. | authorlink2 = Karen Spärck Jones}}</ref> Robertson stated that the assumption of word independence is not justified and exists simply as a matter of mathematical convenience. His objection to the term independence is not a new idea, dating back to at least 1964 when H. H. Williams expressedstated that "[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>
In 2004, Anna Lynn Patterson filed a number of patents on "phrase-based searching in an information retrieval system"<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/20060031195] {{patent|US Patent: |20060031195 }}</ref> to which [[Google ]] subsequently acquired the rights.<ref>[http://www.seobythesea.com/2012/02/google-acquires-cuil-patent-applications/ ] Google Acquires Cuil Patent Applications ]</ref> ▼▲Compound term processing is a new approach to an old problem: how can one improve the relevance of search results while maintaining ease of use? Using this technique, 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. This can be performed by a [[concept search]], which itself uses compound term processing. 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.
== Adaptability ==
▲In 2004, Anna Lynn Patterson filed a number of patents on "phrase-based searching in an information retrieval system"<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/20060031195] US Patent: 20060031195</ref> to which Google subsequently acquired the rights.<ref>[http://www.seobythesea.com/2012/02/google-acquires-cuil-patent-applications/] Google Acquires Cuil Patent Applications</ref>
Statistical compound -term processing is a method more adaptiveadaptable than the process described by Patterson in her patent applications. Her 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 compound term processing is more suited to [[enterprise search]] applications where such [[A priori and a posteriori|a priori]] knowledge is not available.
Statistical compound -term processing is also more adaptiveadaptable than the linguistic approach taken by the CLAMOUR project, which must take into considerationconsider the syntactic properties of the terms (i.e. part of speech, gender, number, etc.) and their combinations. CLAMOUR is highly language-dependent, whereas the statistical approach is language-independent.
== Applications ==
▲Compound -term Term Processingprocessing allows information -retrieval applications, such as [[search engines ]], 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]]s simplyengines looklooked for documents containing the words entered by the user into the search box . These are known as [[keyword search]] engines. [[Boolean search]] engines add a degree of sophistication by allowing the user to specify additional requirements. For example, "Tiger NEAR Woods AND (golf OR golfing) NOT Volkswagen" uses the operators "NEAR", "AND", "OR" and "NOT" to specify that these words must follow certain requirements. A [[ Phrasephrase search]] is simpler to use, but requires that the exact phrase specified appear in the results.
==See also==
* [[Information retrieval]]
== References ==
{{reflist}} or <references />
{{Reflist|30em}}
seed dispersal is done by water , wind , insects and animals
seed dispersal by water
Some plants make use of water to disperse their seeds.
Brooklime
Yellow Water Lily
Mangrove
Although seeds of plants that grow in water are obviously spread by water, there are many other ways in which water plays a part in dispersing seeds.
Plants which grow beside water often rely on water to transport their seeds for them. They may produce light seeds which float, or there may be fluff that helps buoyancy. Two tall trees, Willow and Silver Birch, are often found in the middle of moorland, far from any other trees, but along the course of a stream. They can colonise such isolated places because they both have very small, light seeds, which can be carried by the wind or by water. Foxgloves and Harebells often grow beside streams. They both have light seed that floats.
Trees found on tropical beaches often have their seeds carried there by the sea. They have woody, waterproof coverings which enable them to float in the salty water for long periods. Coconuts are well-known travellers, as is the famous Coco-de-mer, found only on the Seychelles, but familiar before its origin was known from the giant seeds washed up on other tropical beaches.
Mangroves are another familiar tree of tropical beaches. Their seeds are unusual in that they can begin germination while still on the parent plant, and they drop into the ocean when about a foot long. These 'sticks' float upright in the sea, waiting to be flung onto the beach to continue germinating.
Seeds of some tropical trees can even be carried along by ocean currents to land on shores half a world away. Sometimes Sea Beans, the seeds of Entada gigas, are carried from their homes beside rivers in Africa, Australia or South America, across the ocean to land on European shores.
Seeds spread by this method include:
Yellow Flag
Water Mint
Foxglove
Willow
Coconut
Sea Bean
== External links ==
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{{Natural Language Processing}}
{{DEFAULT SORTDEFAULTSORT:Compound Term Processing}}
[[Category:Information retrieval techniques]]
seed dispersal by wind water and all the agents
Flowering plants reproduce themselves by producing seeds. The seeds also provide the plants with a way to spread out and grow in new places, sometimes a long way from the parent. This is important because if the seeds are not dispersed, many germinating seedlings will grow very close to the parent plant. This results in competition between every one of the seedlings as well as with the parent plant. The competition is for light, space, water and nutrients. All of these are important for plants to be able to grow.
Seeds can be dispersed in a number of different ways. They may be carried by wind, water or animals. Some plants even shoot the seeds out explosively. Seed size is an important factor.The seeds of flowering plants vary in size. Some are as small as grains of salt (e.g Foxglove), while others may be almost the size of golfballs (e.g. Horse Chestnut conkers). The difference in size reflects differences in the amount of food reserves stored in the seed for the benefit of the embryo plant inside. Usually, the larger the seed, the more food reserves it contains. This allows the germinating seed and young seedling more time to grow. It can then become well established before it must begin manufacturing its own food. The longer a seedling has before it must become self sufficient, the greater chance it has of becoming successfully established.
However, there is a down-side to having large seeds. The larger and heavier the seed, the more difficult it becomes to disperse it effectively by wind, or explosive techniques. All of these require light seeds. Seeds such as Foxglove are minute and are easily blown about by the wind. Larger wind-dispersed seeds are generally heavier and therefore require features such as parachutes or wings to help keep them aloft. For example, Dandelion seeds have developed very light and fluffy parachute-like structures. These help the seeds to float in the wind and delays their fall to the ground. This delay allows the seeds to be carried further. The largest and heaviest wind-dispersed seeds, such as Sycamore cannot rely on hair-like parachutes to keep them airborne. They would have to be enormous to be effective. Instead they have developed a wing which causes them to spin through the air like mini helicopters. This again delays their fall.
The biggest seeds of all cannot possibly be dispersed by the wind. Large seeds such as nuts, are a valuable food for some animals. They are therefore often dispersed by animals which collect them to eat. Rarely are all such seeds eaten. Some will usually be overlooked, leaving them to germinate wherever they have been left when conditions are right.
The seeds of flowering plants vary in size. Some are as small as grains of salt (e.g Foxglove), while others may be almost the size of golfballs (e.g. Horse Chestnut conkers). The difference in size reflects differences in the amount of food reserves stored in the seed for the benefit of the embryo plant inside. Usually, the larger the seed, the more food reserves it contains. This allows the germinating seed and young seedling more time to grow. It can then become well established before it must begin manufacturing its own food. The longer a seedling has before it must become self sufficient, the greater chance it has of becoming successfully established.
However, there is a down-side to having large seeds. The larger and heavier the seed, the more difficult it becomes to disperse it effectively by wind, or explosive techniques. All of these require light seeds. Seeds such as Foxglove are minute and are easily blown about by the wind. Larger wind-dispersed seeds are generally heavier and therefore require features such as parachutes or wings to help keep them aloft. For example, Dandelion seeds have developed very light and fluffy parachute-like structures. These help the seeds to float in the wind and delays their fall to the ground. This delay allows the seeds to be carried further. The largest and heaviest wind-dispersed seeds, such as Sycamore cannot rely on hair-like parachutes to keep them airborne. They would have to be enormous to be effective. Instead they have developed a wing which causes them to spin through the air like mini helicopters. This again delays their fall.
The biggest seeds of all cannot possibly be dispersed by the wind. Large seeds such as nuts, are a valuable food for some animals. They are therefore often dispersed by animals which collect them to eat. Rarely are all such seeds eaten. Some will usually be overlooked, leaving them to germinate wherever they have been left when conditions are right.
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