Abstract:
The disclosed embodiments relate to data mining methods for determining economically valuable cause effect relationships between objects and properties associated with objects using co-occurrence frequency measurements of semantic terms characterizing observations of properties., effects or behaviors of objects in different environments and using these measurements as object descriptors in calculations determining object similarities. Specifically, these methods may be used to identify new indications of medicines, identify biomarkers associated with disease, identify biomarkers associated with drug effects, quantify disease diagnosis, identify novel drug targets, identify pharmacologic equivalencies of medicines, identify pharmacologic equivalencies between medicines and traditional medicines, identify pharmacologic equivalencies between medicines and Natural products, identify equivalencies between alternate medical procedures, identify risk benefit profiles of medicine combinations, identify targets for antibodies, identify synergies between medicines, identify Side effects of medicines, identify risks of experimental medicines, identify functions of biological networks.
Abstract:
Systems and methods for learning topic models from unstructured data and applying the learned topic models to recognize semantics for new data items are described herein. In at least one embodiment, a corpus of multimedia data items associated with a set of labels may be processed to generate a refined corpus of multimedia data items associated with the set of labels. Such processing may include arranging the multimedia data items in clusters based on similarities of extracted multimedia features and generating intra-cluster and inter-cluster features. The intra-cluster and the inter-cluster features may be used for removing multimedia data items from the corpus to generate the refined corpus. The refined corpus may be used for training topic models for identifying labels. The resulting models may be stored and subsequently used for identifying semantics of a multimedia data item input by a user.
Abstract:
There is provided a method of performing an on-line definition of a first word, the first word received from a user of an electronic device via a communication network. The method can be executed at a server. The method comprises: obtaining a first definition set from a first source, the first definition set being based on the first word; obtaining a second definition set from a second source, the second definition set being based on the first word; parsing the first definition set to obtain individual first set words; parsing the second definition set to obtain individual second set words; organizing the individual first set words into at least one definition cluster; causing the electronic device to display to the user at least the first cluster.
Abstract:
In one example of the disclosure, data indicative of a word or phrase communicated during a meeting including a plurality of participants is obtained. For each participant, records electronically accessible to the participant are identified, and each record is associated with a tier from a hierarchy of record-relevancy tiers. A set of explanations for the communication and associated scores is identified, including for each participant, beginning with a most relevant tier, searching the records accessible to the participant tier by tier until an explanation is identified, and assigning a score to the explanation according to the tier associated with the record in which the explanation is found. A preferred explanation for the communication is determined based upon the scores, and a display of the preferred explanation is caused.
Abstract:
Methods and apparatuses for search are provided and related to the field of search technology. A method may include: performing term segmentation for grabbed documents to count a term frequency of each term, the term frequency of the term representing a number of the grabbed documents containing the term; generating a high frequency term inverted index and a low frequency term inverted index respectively, wherein the high frequency term inverted index contains terms having a term frequency higher than a predefined threshold, and the low frequency term inverted index contains terms having a term frequency not higher than the predefined threshold; and loading the high frequency term inverted index and the low frequency term inverted index respectively to different retrieval modules, the different retrieval modules respectively corresponding to mutually independent storage devices.
Abstract:
Systems and methods provide natural language search results to clearintent queries. To provide the natural language search results, a system may parse a document from an authoritative source to generate at least one headingtext pair, the text appearing under the heading in the document. The system may assign a topic and a question category to the heading-text pair and store the heading-text pair in a data store keyed by the topic and the question category. The system determines that a query corresponds to the topic and the question category, and provides the heading-text pair as a natural language search result for the query. In some implementations, the text portion of the heading-text pair may be a paragraph or a list of items and the natural language search result may be provided with conventional snippet-based search results in response to the query.
Abstract:
A method for generating a medical suggestion useful for supporting a process of medical decision making is presented. A database with a particular, advantageous structure and content allows for the efficient evaluation of received known medical facts based on a set based processing and calculation. Thus, a digital, automatic, and holistic method generating a medical suggestion is provided, which increases the reliability of the selected medical suggestion which is provided to the user as most probable. The structure of the herein provided database provides for maintenance advantages of the database as the complexity is reduced and single structures of the database are manageable and easily understandable. A corresponding medical decision support system is presented as well.
Abstract:
Disclosed in some examples is a method comprising determining a first set of high ranking skills, the first set containing skills possessed by a member of the social networking service based upon the member's user profile; determining a second set of high ranking skills, the second set containing skills for a second member of the social networking service based on the second member's user profile; determining a third set of high ranking skills, the third set being the intersection between the first and second set of high ranking skills; and suggesting one or more of the skills in the third set of high ranking skills to the member for endorsement of the second member with respect to that skill.