Abstract: This invention provides a method for extracting a diagnosis object from a medical document comprises: extracting, from an input medical document, body part entities and at least one type of non-body-part entities and the relations between the body part entities and the non-body-part entities; obtaining, for each pair of all possible pairs of the non-body-part entities, a relevance score between two non-body-part entities within one pair, wherein the relevance score is obtained by using the relations between the two non-body-part entities within one pair and one or more body part entities in a plurality of historical medical documents; clustering the non-body-part entities in the input medical document into one or more clusters based on the relevance scores of the all possible pairs; and outputting one or more body part entities related to one or more non-body-part entities clustered in each of the clusters as one diagnosis object.

Abstract: This invention provides a method for extracting a diagnosis object from a medical document comprises: extracting, from an input medical document, body part entities and at least one type of non-body-part entities and the relations between the body part entities and the non-body-part entities; obtaining, for each pair of all possible pairs of the non-body-part entities, a relevance score between two non-body-part entities within one pair, wherein the relevance score is obtained by using the relations between the two non-body-part entities within one pair and one or more body part entities in a plurality of historical medical documents; clustering the non-body-part entities in the input medical document into one or more clusters based on the relevance scores of the all possible pairs; and outputting one or more body part entities related to one or more non-body-part entities clustered in each of the clusters as one diagnosis object.

Abstract: This invention provides methods and apparatuses for segmenting text. A method for segmenting a text including a plurality of sentences comprises: extracting a plurality of evidences and a plurality of inferences from the text; for each of said inferences, determining a preferred position for each of said evidences based on the text and/or segmentation histories, wherein the preferred position represents the position that the evidence is the most likely to take in a sequence of evidences which are used to make the inference; and segmenting the text into a plurality of sections by determining one or more of boundaries between every two consecutive sentences in the text as section boundaries based on the preferred positions for the evidences. By virtue of the present invention, the segmentation will be more accurate.

Abstract: This application relates to a method and apparatus for identifying a mentioned person in a dialog. A method for identifying a mentioned person in a dialog, comprising: identifying at least one person name entity associated with a mentioned person name which is acquired from the dialog; acquiring a group of candidate identifiers associated with the mentioned person name; acquiring at least one relation feature for each of the candidate identifiers from internal resources and external resources, wherein the relation feature refers to the relation between the candidate identifier and the at least one person name entity; and selecting an identifier from the group of candidate identifiers as the identifier of the mentioned person name based on the at least one relation feature. According to the method and the apparatus of the present invention, a mentioned person can be accurately identified.