Abstract: Methods and systems for entity recognition and disambiguation using natural language processing techniques are provided. Example embodiments provide an entity recognition and disambiguation system (ERDS) and process that, based upon input of a text segment, automatically determines which entities are being referred to by the text using both natural language processing techniques and analysis of information gleaned from contextual data in the surrounding text. In at least some embodiments, supplemental or related information that can be used to assist in the recognition and/or disambiguation process can be retrieved from knowledge repositories such as an ontology knowledge base. In one embodiment, the ERDS comprises a linguistic analysis engine, a knowledge analysis engine, and a disambiguation engine that cooperate to identify candidate entities from a knowledge repository and determine which of the candidates best matches the one or more detected entities in a text segment using context information.

Abstract: Systems and methods of a knowledge management networking are disclosed here. In one aspect, embodiments of the present disclosure include a method, which may be implemented on a system, of hosting a web-space having a plurality of objects, the plurality of objects to include one or more of, representations of a set of users, a set of web-items, and a set of nets; wherein a net of the set of nets is a subset of the web-space comprising a sub-plurality of the plurality of objects.

Abstract: An application that enables users to effectively utilize and manage knowledge and data the user posses and allows other users to effectively and seamlessly benefit from the user's knowledge and data over a computer network is also disclosed. A method of processing content created by a user utilizing a semantic, ontology-driven portal on a computer network is described. The semantic portal application provides the user with a content base, such as a semantic form or meta-form, for creating a semantic posting. The semantic portal utilizes a knowledge data structure, such as a taxonomy or ontology, in preparing a semantic posting based on the information provided by the user via the content base. The semantic portal application prepares a preview of a semantic posting for evaluation by the user. The semantic posting is then either modified by the user or accepted and posted by the user for external parties to view.

Abstract: Among other disclosure, a knowledge network and semcards enabling intelligent matching of offers and requests, involving all types of information and knowledge, including information such as classified ads, data about products and services, or knowledge, expertise, ideas, suggestions, opinions, and other forms of tacit knowledge is described.

Abstract: The patent describes a single location and application on a network where a user can organize public, group, and private/personal information and have this single, location accessible to the public. A new, ontology-driven portal that organizes all three categories of data according to various “facets” using underlying ontologies to define each “facet” and wherein any type of information can be classified and linked to other types of information is disclosed. An application that enables a user to effectively utilize and manage knowledge and data the user posses and allows other users to effectively and seamlessly benefit from the user's knowledge and data over a computer network is also disclosed. A method of processing content created by a user utilizing a semantic, ontology-driven portal on a computer network is described. The semantic portal application provides the user with a content base, such as a semantic form or meta-form, for creating a semantic posting.

Abstract: Systems and methods for automatic mapping of a location identifier pattern of an object to a semantic type using object metadata are disclosed. In one aspect, embodiments of the present disclosure include a method, which may be implemented on a system, of identifying a set of tags associated with a website that is hosted by a web server. The method further includes, detecting a web page in the website in which a tag of the set of tags is identified, extracting a pattern from a Universal Resource Locator (URL) of the web page, and/or storing the pattern in a database embodied in a machine-readable storage medium as being mapped to the semantic type. The tag corresponds to a semantic type with which the content embodied in the web page has a semantic relationship and the pattern corresponds to the semantic type with which the content embodied in the web page has a semantic relationship.

Abstract: Among other disclosure, a knowledge network and semcards enabling intelligent matching of offers and requests, involving all types of information and knowledge, including information such as classified ads, data about products and services, or knowledge, expertise, ideas, suggestions, opinions, and other forms of tacit knowledge is described.

Abstract: Enhanced computer- and network-based methods, systems, techniques are provided for retrieving more accurate and responsive search results when searching content for a designated entity using an off-the-shelf keyword-based search engine. For example, the embodiments described herein may be used to improve search results by eliminating off-topic results when presenting queries to an existing keyword-based search engine invoked by means of an API from an intermediating application. Example embodiments provide a Keyword-Based Search Enhancement System (“KBSES”), which enables intermediating applications to obtain information more closely related to user queries by enhancing such queries, on behalf of the user, with disambiguating information when deemed necessary.

Abstract: Methods, techniques, and systems for advertisement targeting are provided. Example embodiments provide an enhanced ad targeting system (“EATS”), which given one or more products, determines keywords to associate with those products and which, given one or more entities, determines related products for which ads can be targeted. In some embodiments, the EATS uses semantic analysis and relationship searching to aid in the selection of ads more relevant to a context or search query.

Abstract: Methods and systems for extending keyword searching techniques to syntactically and semantically annotated data are provided. Example embodiments provide a Syntactic Query Engine (“SQE”) that parses, indexes, and stores a data set as an enhanced document index with document terms as well as information pertaining to the grammatical roles of the terms and ontological and other semantic information. In one embodiment, the enhanced document index is a form of term-clause index, that indexes terms and syntactic and semantic annotations at the clause level. The enhanced document index permits the use of a traditional keyword search engine to process relationship queries as well as to process standard document level keyword searches. In one embodiment, the SQE comprises a Query Processor, a Data Set Preprocessor, a Keyword Search Engine, a Data Set Indexer, an Enhanced Natural Language Parser (“ENLP”), a data set repository, and, in some embodiments, a user interface or an application programming interface.

Abstract: Methods and systems for syntactically indexing and searching data sets to achieve more accurate search results and for indexing and searching data sets using entity tags alone or in combination therewith are provided. Example embodiments provide a Syntactic Query Engine (“SQE”) that parses, indexes, and stores a data set, as well as processes natural language queries subsequently submitted against the data set. The SQE comprises a Query Preprocessor, a Data Set Preprocessor, a Query Builder, a Data Set Indexer, an Enhanced Natural Language Parser (“ENLP”), a data set repository, and, in some embodiments, a user interface. After preprocessing the data set, the SQE parses the data set according to a variety of levels of parsing and determines as appropriate the entity tags and syntactic and grammatical roles of each term to generate enhanced data representations for each object in the data set. The SQE indexes and stores these enhanced data representations in the data set repository.