Abstract: The present invention may be a method, a computer system, and a computer program product for suggesting an output candidate. The method comprises receiving a user input; selecting a corpus containing an expression similar to the user input among a plurality of corpuses; finding, in the user input, a seed word that may be present in a definition statement of an entry in a dictionary; identifying, in the dictionary, an entry of a definition statement containing the seed word or within a threshold similarity to the seed word with reference to the selected corpus; and suggesting the identified entry as an output candidate.

Abstract: The present inventive concept provided for context aware speech transcription. The method includes obtaining speech corpora for a target domain. A corrected speech corpora is created by editing misused words in the speech corpora with correct words for the target domain. The training sets are prepared based on the speech corpora and corrected speech corpora, and an optimal percentage of the training sets to use for accurate transcription of speech related to the target domain is determined.

Abstract: A system and method for expanding a question and answer (Q&A) database. The method includes obtaining a set of Q&A documents and speech recognition results, each Q&A document in the set having an identifier, and each speech recognition result having an identifier common with the identifier of a relevant Q&A document, and adding one or more repetition parts extracted from the speech recognition results to a corresponding Q&A document in the set to generate an expanded set of Q&A documents for increasing Q&A document extraction accuracy.

Abstract: A method, a system, and a computer program product for predicting an outcome expected for a particular positional value is provided. In the method, an input set of data records, each having a label and a positional value, and a target positional value are obtained. The label of each data record is one in a label set. A learning model that includes an output layer, an input layer corresponding to the label set and a network structure provided therebetween is read. In the learning model, the network structure has a plurality of functions trained so as to evaluate influence from each label in the label set depending on a relationship between the target positional value and a representative positional value associated with the label in the label set. A target outcome is estimated for the target positional value from the input set using the learning model.

Abstract: Within a first image in a set of images comprising a panoramic view of a scene, a first boundary feature is identified using a model. Within the first boundary feature, a first set of points is selected. Within a second image in the set of images, a second boundary feature is identified using the model. Within the second boundary feature, a second set of points is selected. A set of parameters of a geometrical shape including the first set of points and the second set of points is determined. From the first image and the second image, a panoramic image is formed, the first image placed within the panoramic image according to the position of the first image on the geometrical shape, the second image placed in the panoramic image according to the position of the second image on the geometrical shape.

Abstract: A computer retrieves a dialog information records of the active call of the first operator. The computer extracts features from the dialog information records. The computer determines a feature vector from the extracted features and determines a transfer probability value based on the feature vector and previous call transfers to the second operator.

Abstract: Systems and methods are provided for recognizing pathological images captured by alternate image capturing devices. In embodiments, a computer-implemented method includes: obtaining, by a computing device, a classifier generated based on a plurality of standardized training pathology images associated with a known classification and generated by a first type of device; receiving, by the computing device, an alternate pathology image captured by a second type of device; standardizing, by the computing device, the alternate pathology image; determining, by the computing device, a classification of the alternate pathology image based on applying the generated classifier; and outputting, by the computing device, information regarding the determined classification to aid in diagnosis of a medical condition represented by the alternate pathology image.

Abstract: A method of creating a presentation includes extracting text parts from content, assigning first attributes to the text parts based on the content and design similarities between the text parts, assigning second attributes to the text parts based on processing the text content to extract contextual similarities between the text parts, determining groups of the text parts based on the first and second attributes, determining first links between the text parts of different groups using the display information and adjacencies of the text parts, determining second links of the text parts to object types defined by a graph restriction listing the object types and their parameters, and outputting a presentation by setting the text parts in the presentation corresponding to the parameters of their linked object type in the graph restriction, wherein the text parts of each of the groups are associated with a same one of the object types.

Abstract: A computer retrieves a dialog information records of the active call of the first operator. The computer extracts features from the dialog information records. The computer determines a feature vector from the extracted features and determines a transfer probability value based on the feature vector and previous call transfers to the second operator.

Abstract: Within a first image in a set of images comprising a panoramic view of a scene, a first boundary feature is identified using a model. Within the first boundary feature, a first set of points is selected. Within a second image in the set of images, a second boundary feature is identified using the model. Within the second boundary feature, a second set of points is selected. A set of parameters of a geometrical shape including the first set of points and the second set of points is determined. From the first image and the second image, a panoramic image is formed, the first image placed within the panoramic image according to the position of the first image on the geometrical shape, the second image placed in the panoramic image according to the position of the second image on the geometrical shape.

Abstract: A computer retrieves a dialog information records of the active call of the first operator. The computer extracts features from the dialog information records. The computer determines a feature vector from the extracted features and determines a transfer probability value based on the feature vector and previous call transfers to the second operator.

Abstract: A computer retrieves a dialog information records of the active call of the first operator. The computer extracts features from the dialog information records. The computer determines a feature vector from the extracted features and determines a transfer probability value based on the feature vector and previous call transfers to the second operator.

Abstract: Systems and methods are provided for recognizing pathological images captured by alternate image capturing devices. In embodiments, a computer-implemented method includes: obtaining, by a computing device, a classifier generated based on a plurality of standardized training pathology images associated with a known classification and generated by a first type of device; receiving, by the computing device, an alternate pathology image captured by a second type of device; standardizing, by the computing device, the alternate pathology image; determining, by the computing device, a classification of the alternate pathology image based on applying the generated classifier; and outputting, by the computing device, information regarding the determined classification to aid in diagnosis of a medical condition represented by the alternate pathology image.

Abstract: The present invention may be a method, a computer system, and a computer program product for suggesting an output candidate. The method comprises receiving a user input; selecting a corpus containing an expression similar to the user input among a plurality of corpuses; finding, in the user input, a seed word that may be present in a definition statement of an entry in a dictionary; identifying, in the dictionary, an entry of a definition statement containing the seed word or within a threshold similarity to the seed word with reference to the selected corpus; and suggesting the identified entry as an output candidate.

Abstract: Systems and methods are provided for recognizing pathological images captured by alternate image capturing devices. In embodiments, a computer-implemented method includes: obtaining, by a computing device, a classifier generated based on a plurality of standardized training pathology images associated with a known classification and generated by a first type of device; receiving, by the computing device, an alternate pathology image captured by a second type of device; standardizing, by the computing device, the alternate pathology image; determining, by the computing device, a classification of the alternate pathology image based on applying the generated classifier; and outputting, by the computing device, information regarding the determined classification to aid in diagnosis of a medical condition represented by the alternate pathology image.

Abstract: A system including: a text analyzing unit extracting keywords as predetermined facets from text of a document to define a time sequence of a part of the text between the keywords and sort words included in the part into time axes, the time axes being divisions of the time sequence; and a drawing unit drawing a chart in a drawing space, the chart including nodes and an edge, the nodes corresponding to the facets, the nodes being arranged in the drawing space in accordance with a relationship of the time sequence between the facets, the edge being linked to the nodes in accordance with a connection between the facets.

Abstract: Systems and methods are provided for recognizing pathological images captured by alternate image capturing devices. In embodiments, a computer-implemented method includes: obtaining, by a computing device, a classifier generated based on a plurality of standardized training pathology images associated with a known classification and generated by a first type of device; receiving, by the computing device, an alternate pathology image captured by a second type of device; standardizing, by the computing device, the alternate pathology image; determining, by the computing device, a classification of the alternate pathology image based on applying the generated classifier; and outputting, by the computing device, information regarding the determined classification to aid in diagnosis of a medical condition represented by the alternate pathology image.

Abstract: A system and method for expanding a question and answer (Q&A) database. The method includes obtaining a set of Q&A documents and speech recognition results, each Q&A document in the set having an identifier, and each speech recognition result having an identifier common with the identifier of a relevant Q&A document, and adding one or more repetition parts extracted from the speech recognition results to a corresponding Q&A document in the set to generate an expanded set of Q&A documents for increasing Q&A document extraction accuracy.

Abstract: A system and method for expanding a question and answer (Q&A) database. The method includes preparing a set of Q&A documents and speech recognition results of an agent's utterances in conversations between an agent and a customer, each Q&A document in the set having an identifier, and each speech recognition result having an identifier common with the identifier of a relevant Q&A document, and adding one or more repetition parts extracted from the speech recognition results of the agent's utterances to a corresponding Q&A document in the set.

Abstract: A method, a system, and a computer program product for predicting an outcome expected for a particular positional value is provided. In the method, an input set of data records each having a label and a positional value, and a target positional value are obtained. The label of each data record is one in a label set. A learning model that includes an output layer, an input layer corresponding to the label set and a network structure provided therebetween is read. In the learning model, the network structure has a plurality of functions trained so as to evaluate influence from each label in the label set depending on relationship between the target positional value and a representative positional value associated with the label in the label set. A target outcome is estimated for the target positional value from the input set using the learning model.