Package org.carrot2.core

Examples of org.carrot2.core.Controller.process()

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    for (int i = 0; i < titles.length; i++) {
      Document doc = new Document(titles[i], snippets[i],
              "file://foo_" + i + ".txt");
      documents.add(doc);
    }
    final ProcessingResult result = controller.process(documents,
            "red fox",
            LingoClusteringAlgorithm.class);//<co id="crt2.process"/>
    displayResults(result);//<co id="crt2.print"/>

    /*
 
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            /* Put your own API key here! */
            attributes.put(Bing3WebDocumentSourceDescriptor.Keys.APPID, BingKeyAccess.getKey());
           
            /* Perform processing */
            final ProcessingResult result = controller.process(attributes,
                Bing3WebDocumentSource.class, LingoClusteringAlgorithm.class);
   
            /* Documents fetched from the document source, clusters created by Carrot2. */
            final List<Document> documents = result.getDocuments();
            final List<Cluster> clusters = result.getClusters();
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            Bing3WebDocumentSourceDescriptor
                .attributeBuilder(attributes)
                    .appid(BingKeyAccess.getKey()); // use your own key here
           
            /* Perform processing */
            final ProcessingResult result = controller.process(attributes,
                Bing3WebDocumentSource.class, LingoClusteringAlgorithm.class);
   
            /* Documents fetched from the document source, clusters created by Carrot2. */
            final List<Document> documents = result.getDocuments();
            final List<Cluster> clusters = result.getClusters();
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                    .desiredClusterCountBase(15)
                    .matrixReducer()
                        .factorizationQuality(FactorizationQuality.HIGH);

            /* Perform processing */
            final ProcessingResult result = controller.process(attributes,
                LingoClusteringAlgorithm.class);
           
            /* Clusters created by Carrot2, read processing time */
            final List<Cluster> clusters = result.getClusters();
            final Long clusteringTime = CommonAttributesDescriptor.attributeBuilder(
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            /// [[[start:clustering-data-from-document-sources-simple]]]
            /* A controller to manage the processing pipeline. */
            final Controller controller = ControllerFactory.createSimple();

            /* Perform processing */
            final ProcessingResult result = controller.process("data mining", 100,
                EToolsDocumentSource.class, LingoClusteringAlgorithm.class);
   
            /* Documents fetched from the document source, clusters created by Carrot2. */
            final List<Document> documents = result.getDocuments();
            final List<Cluster> clusters = result.getClusters();
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            /* Query an the required number of results */
            attributes.put(CommonAttributesDescriptor.Keys.QUERY, "clustering");
            attributes.put(CommonAttributesDescriptor.Keys.RESULTS, 50);
   
            /* Perform processing */
            final ProcessingResult result = controller.process(attributes,
                Bing3WebDocumentSource.class, STCClusteringAlgorithm.class);

            /* Documents fetched from the document source, clusters created by Carrot2. */
            final List<Document> documents = result.getDocuments();
            final List<Cluster> clusters = result.getClusters();
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        }

        final Map<String, Object> attributes = Maps.newHashMap();
        CommonAttributesDescriptor.attributeBuilder(attributes)
            .documents(documents);
        final ProcessingResult englishResult = controller.process(
            attributes, LingoClusteringAlgorithm.class);
        ConsoleFormatter.displayResults(englishResult);

        /*
         * In the second call, we will fetch results for a Chinese query from Bing,
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            .market(MarketOption.CHINESE_CHINA);
        Bing3WebDocumentSourceDescriptor
            .attributeBuilder(attributes)
                .appid(BingKeyAccess.getKey()); // use your own ID here!

        final ProcessingResult chineseResult = controller.process(attributes,
            Bing3WebDocumentSource.class, LingoClusteringAlgorithm.class);
        ConsoleFormatter.displayResults(chineseResult);

        /*
         * In the third call, we will fetch results for the same Chinese query from
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            .results(100);

        MultilingualClusteringDescriptor.attributeBuilder(attributes)
            .defaultLanguage(LanguageCode.CHINESE_SIMPLIFIED);

        final ProcessingResult chineseResult2 = controller.process(attributes,
            GoogleDocumentSource.class, LingoClusteringAlgorithm.class);
        ConsoleFormatter.displayResults(chineseResult2);
        // [[[end:clustering-non-english-content]]]
    }
}
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        /*
         * We need to refer to the Lucene component by its identifier we set during
         * initialization. As we've not assigned any identifier to the
         * LingoClusteringAlgorithm we want to use, we can its fully qualified class name.
         */
        ProcessingResult process = controller.process(
            processingAttributes, "lucene", LingoClusteringAlgorithm.class.getName());

        ConsoleFormatter.displayResults(process);
    }
   
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