Abstract: A probabilistic clustering system is defined at least in part by probabilistic model parameters indicative of word counts, ratios, or frequencies characterizing classes of the clustering system. An association of one or more documents in the probabilistic clustering system is changed from one or more source classes to one or more destination classes. Probabilistic model parameters characterizing classes affected by the changed association are locally updated without updating probabilistic model parameters characterizing classes not affected by the changed association.

Abstract: Documents are clustered or categorized to generate a model associating documents with classes. Outlier measures are computed for the documents indicative of how well each document fits into the model. Outlier documents are identified to a user based on the outlier measures and a user selected outlier criterion. Ambiguity measures are computed for the documents indicative of a number of classes with which each document has similarity under the model. If a document is annotated with a label class, a possible corrective label class is identified if the annotated document has higher similarity with the possible corrective label class under the model than with the annotated label class. The clustering or categorizing is repeated adjusted based on received user input to generate an updated model associating documents with classes. Outlier and ambiguity measures are also calculated at runtime for new documents classified using the model.

Abstract: A multimedia information retrieval system includes a storage and an electronic processing device. The latter is configured to perform a process including: computing values of a pairwise similarity measure quantifying pairwise similarity of documents of a multimedia reference repository; storing the computed values in the storage; performing an initial information retrieval process respective to the multimedia reference repository to return a set of initial repository documents; and identifying a set of top ranked documents of the multimedia reference repository based at least on the stored computed values pertaining to the set of initial repository documents.

Abstract: Cross-lingual information retrieval is disclosed, comprising: translating a received query from a source natural language into a target natural language; performing a first information retrieval operation on a corpus of documents in the target natural language using the translated query to retrieve a set of pseudo-feedback documents in the target natural language; re-translating the received query from the source natural language into the target natural language using a translation model derived from the set of pseudo-feedback documents in the target natural language; and performing a second information retrieval operation on the corpus of documents in the target natural language using the re-translated query to retrieve an updated set of documents in the target natural language

Abstract: A calibrated categorizer comprises: a multi-class categorizer configured to output class probabilities for an input object corresponding to a set of classes; a class probabilities rescaler configured to rescale class probabilities to generate rescaled class probabilities; and a resealing model learner configured to learn calibration parameters for the class probabilities rescaler based on (i) class probabilities output by the multi-class categorizer for a calibration set of class-labeled objects, (ii) confidence measures output by the multi-class categorizer for the calibration set of class-labeled objects, and (iii) class labels of the calibration set of class-labeled objects, the class probabilities rescaler calibrated by the learned calibration parameters defining a calibrated class probabilities rescaler.

Abstract: In categorizing an object respective to at least two categorization dimensions each defined by a plurality of categories, a probability value indicative of the object is determined for each category of each categorization dimension. A categorization label for the object is selected respective to each categorization dimension based on (i) the determined probability values of the categories of that categorization dimension and (ii) the determined probability values of categories of at least one other of the at least two categorization dimensions.

Abstract: Various methods formulated using a geometric interpretation for identifying bilingual pairs in comparable corpora using a bilingual dictionary are disclosed. The methods may be used separately or in combination to compute the similarity between bilingual pairs.

Abstract: Documents are clustered or categorized to generate a model associating documents with classes. Outlier measures are computed for the documents indicative of how well each document fits into the model. Outlier documents are identified to a user based on the outlier measures and a user selected outlier criterion. Ambiguity measures are computed for the documents indicative of a number of classes with which each document has similarity under the model. If a document is annotated with a label class, a possible corrective label class is identified if the annotated document has higher similarity with the possible corrective label class under the model than with the annotated label class. The clustering or categorizing is repeated adjusted based on received user input to generate an updated model associating documents with classes. Outlier and. ambiguity measures are also calculated at runtime for new documents classified using the model.

Abstract: A method for enrichment of text which enables mixed data mining includes generating a model for structured data found in tables of a database. In the model, semantically-linked terms are associated with referents, such as field names or cell content of the fields, of the structured data. The referents may be a business object or refer to a business object. A plurality of candidate referring entities in textual data in the database, such as chunks of free text, is identified. For each candidate referring entity, a similarity measure between the candidate referring entity in the textual data and the model is computed to identify referring entities of the candidate referring entities and corresponding business objects/referents to which the referring entities refer. The textual data is enriched with information derived from the business objects.

Abstract: A probabilistic clustering system is defined at least in part by probabilistic model parameters indicative of word counts, ratios, or frequencies characterizing classes of the clustering system. An association of one or more documents in the probabilistic clustering system is changed from one or more source classes to one or more destination classes. Probabilistic model parameters characterizing classes affected by the changed association are locally updated without updating probabilistic model parameters characterizing classes not affected by the changed association.

Abstract: In categorizing an object respective to at least two categorization dimensions each defined by a plurality of categories, a probability value indicative of the object is determined for each category of each categorization dimension. A categorization label for the object is selected respective to each categorization dimension based on (i) the determined probability values of the categories of that categorization dimension and (ii) the determined probability values of categories of at least one other of the at least two categorization dimensions.

Abstract: Various methods formulated using a geometric interpretation for identifying bilingual pairs in comparable corpora using a bilingual dictionary are disclosed. The methods may be used separately or in combination to compute the similarity between bilingual pairs.