Abstract: Systems, methods, and computer-readable storage media for detecting shifts in intent for search queries are provided. The system includes databases and servers. The databases store search logs and entity mappings. The servers merge the entity mappings with search logs, identify shifts in intent for recurring queries in the search log, identify intents for new queries in the search log, and updates mappings between an entity and a query based on the shifted intents. The server may provide client devices that display a search box where queries are entered. The search box may include an autosuggest area that is updated to include spiking entities or spiking queries.

Abstract: Concept disambiguation is provided for search queries by analyzing search results in conjunction with an ontology of concepts. An ontology of concepts is identified, and at least one document is associated with each concept. The document associated with a concept is representative of the concept and used to generate a concept signature. When a search query is received, it is processed to obtain search results. The search results are used to generate a search results signature, which is compared to the concept signatures to identify one or more concepts that are relevant to the search query.

Abstract: Referring expressions are identified for concepts by analyzing search query and result selection information. An ontology of concepts is identified, and at least one document is associated with each concept. The document associated with a concept is representative of the concept. Search query information from a search engine is analyzed to identify search queries that resulted in user selections of documents associated with the concepts. Referring expressions that refer to the concepts are identified based on the search queries that resulted in user selections of documents corresponding with the concepts. After identifying referring expressions for concepts, search queries may be mapped to referring expressions to identify concepts to which the search queries pertain, and search result pages may be generated based on knowledge of the concepts.

Abstract: Concept disambiguation is provided for search queries by analyzing search results in conjunction with an ontology of concepts. An ontology of concepts is identified, and at least one document is associated with each concept. The document associated with a concept is representative of the concept and used to generate a concept signature. When a search query is received, it is processed to obtain search results. The search results are used to generate a search results signature, which is compared to the concept signatures to identify one or more concepts that are relevant to the search query.

Abstract: Referring expressions are identified for concepts by analyzing search query and result selection information. An ontology of concepts is identified, and at least one document is associated with each concept. The document associated with a concept is representative of the concept. Search query information from a search engine is analyzed to identify search queries that resulted in user selections of documents associated with the concepts. Referring expressions that refer to the concepts are identified based on the search queries that resulted in user selections of documents corresponding with the concepts. After identifying referring expressions for concepts, search queries may be mapped to referring expressions to identify concepts to which the search queries pertain, and search result pages may be generated based on knowledge of the concepts.

Abstract: A facial detection module detects faces in any frame in a video by applying at least two rectangles between the eyes of a face and other regions and calculating a difference in intensity between those regions. The intensities are used to generate face detections. A tracking module predicts the location of faces in frames across time and compares the predicted location to the face detections. The face detection that is closest to the predicted location is selected, provided that it exceeds a threshold of overlap with the predicted location. A tracking module determines shot boundaries by comparing the similarities between frames. A clustering module groups the face tracks in the shots, as demarcated by the shot boundaries, for individuals within the video. A body detection module attaches a body outline to each of the face tracks to increase the clickable area for the individuals.