solr自动聚类,solr聚类
solr自动聚类,solr聚类
Solr 使用Carrot2完成了聚类功能,能够把检索到的内容自动分类, Carrot2聚类示例:要想Solr支持聚类功能,首选要把Solr发行包的中的dist/ solr-clustering-4.2.0.jar, 复制到\solr\contrib\analysis-extras\lib下.然后打开solrconfig.xml进行添加配置:
<searchComponent name="clustering"
enable="${solr.clustering.enabled:true}"
class="solr.clustering.ClusteringComponent" >
<lst name="engine">
<str name="name">default</str>
<str name="carrot.algorithm">org.carrot2.clustering.lingo.LingoClusteringAlgorithm</str>
<str name="LingoClusteringAlgorithm.desiredClusterCountBase">30</str><!--2~100-->
<str name="LingoClusteringAlgorithm.clusterMergingThreshold">0.70</str><!--0~1-->
<str name="LingoClusteringAlgorithm.scoreWeight">0</str><!--0~1-->
<str name="LingoClusteringAlgorithm.labelAssigner">org.carrot2.clustering.lingo.SimpleLabelAssigner</str><!--org.carrot2.clustering.lingo.UniqueLabelAssigner -->
<str name="LingoClusteringAlgorithm.phraseLabelBoost">1.5</str><!--0~10-->
<str name="LingoClusteringAlgorithm.phraseLengthPenaltyStart">8</str><!--2~8-->
<str name="LingoClusteringAlgorithm.phraseLengthPenaltyStop">8</str><!--2~8-->
<str name="TermDocumentMatrixReducer.factorizationQuality">HIGH</str><!--LOW,MEDIUM,HIGH--> <!-- org.carrot2.matrix.factorization.PartialSingularValueDecompositionFactory org.carrot2.matrix.factorization.NonnegativeMatrixFactorizationEDFactory org.carrot2.matrix.factorization.NonnegativeMatrixFactorizationKLFactory org.carrot2.matrix.factorization.LocalNonnegativeMatrixFactorizationFactory org.carrot2.matrix.factorization.KMeansMatrixFactorizationFactory --> <str name="TermDocumentMatrixReducer.factorizationFactory">org.carrot2.matrix.factorization.NonnegativeMatrixFactorizationEDFactory</str> <str name="TermDocumentMatrixBuilder.maximumMatrixSize">37500</str><!--MinValue5000--> <str name="TermDocumentMatrixBuilder.titleWordsBoost">2.0</str><!--2~10--> <str name="TermDocumentMatrixBuilder.maxWordDf">0.9</str><!--0~1--> <!--org.carrot2.text.vsm.LogTfIdfTermWeighting,org.carrot2.text.vsm.LinearTfIdfTermWeighting--> <str name="TermDocumentMatrixBuilder.termWeighting">org.carrot2.text.vsm.TfTermWeighting</str> <str name="MultilingualClustering.defaultLanguage">CHINESE_SIMPLIFIED</str> <str name="MultilingualClustering.languageAggregationStrategy">org.carrot2.text.clustering.MultilingualClustering.LanguageAggregationStrategy.FLATTEN_MAJOR_LANGUAGE </str><!--FLATTEN_ALL,FLATTEN_NONE--> <str name="GenitiveLabelFilter.enabled">true</str> <str name="StopWordLabelFilter.enabled">true</str> <str name="NumericLabelFilter.enabled">true</str> <str name="QueryLabelFilter.enabled">true</str> <str name="MinLengthLabelFilter.enabled">true</str> <str name="StopLabelFilter.enabled">true</str> <str name="CompleteLabelFilter.enabled">true</str> <str name="CompleteLabelFilter.labelOverrideThreshold">0.65</str><!--0~1--> <str name="DocumentAssigner.exactPhraseAssignment">false</str> <str name="DocumentAssigner.minClusterSize">2</str><!--1~100--> <str name="merge-resources">true</str> <str name="CaseNormalizer.dfThreshold">1</str><!--1~100--> <str name="PhraseExtractor.dfThreshold">1</str><!--1~100--> <str name="carrot.lexicalResourcesDir">clustering/carrot2</str> <str name="SolrDocumentSource.solrIdFieldName">id</str> </lst> </searchComponent> |
配好了聚类组件后,下面配置requestHandler:
<requestHandler name="/clustering"
startup="lazy"
enable="${solr.clustering.enabled:true}"
class="solr.SearchHandler">
<lst name="defaults">
<str name="echoParams">explicit</str>
<bool name="clustering">true</bool>
<str name="clustering.engine">default</str>
<bool name="clustering.results">true</bool>
<str name="carrot.title">category_s</str>
<str name="carrot.snippet">content</str>
<str name="carrot.url">path</str>
<str name="carrot.produceSummary">true</str>
</lst>
<arr name="last-components">
<str>clustering</str>
</arr>
</requestHandler>
|
有两个参数要注意carrot.title,carrot.snippet是聚类的比较计算字段,这两个参数必须是stored="true".carrot.title的权重要高于carrot.snippet,如果只有一个做计算的字段carrot.snippet可以去掉(是去掉不是值为空).设完了用下面的URL就可以查询了 http://localhost:8080/skyCore/clustering?q=*%3A*&wt=xml&indent=true 更多精彩内容请关注:http://bbs.superwu.cn 关注超人学院微信二维码: 关注超人学院java免费学习交流群:
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