264 results about "Semantic Web" patented technology

Semantically linked pages are queried based on a user supplied interest vector. The interest vector provides a weight for presenting results from the query of pages. The interest vectors are used to calculate the importance of pages of a query based on the weight of semantic links associated with the page known as page rank indicators. Optionally, the calculation is augmented by other page ranking algorithms. An indication of the resulting pages is displayed according to the calculated importance. Preferably the calculation utilizes a dot product of page rank and user interest vectors.

In the realm of managing relational databases, a system that uses both the data in a relational database and domain knowledge in ontologies to return semantically relevant results to a user's query. Broadly contemplated herein, in essence, is a system that bridges a semantic gap between queries users want to express and queries that can be answered by the database using domain knowledge contained in ontologies. In accordance with a preferred embodiment of the present invention, such a system extends relational databases with the ability to answer semantic queries that are represented in SPARQL, an emerging Semantic Web query language. Particularly, users may express their queries in SPARQL, based on a semantic model of the data, and they get back semantically relevant results. Also broadly contemplated herein is the definition of different categories of results that are semantically relevant to a user's query and an effective retrieval of such results.

An Internet search system integrates additional concept-related information into a regular web search engine, providing better page ranking and richer presentation of search results. The additional information is directly related to the contents of the retrieved web pages but does not appear on the retrieved web pages and / or in the link structure. The new search system searches a conventional web page collection together with databases containing publications and semantic web data, which provides the aforesaid additional information.

Semantic understanding of hypotheses returned by a speech engine could improve the quality of recognition and in cases of misrecognition speed the identification of errors and potential substitutions. Unfortunately, semantic recognition using natural language parsers is hard since semantic and syntactic rules for processing language are complex and computationally expensive. Additionally, semantic recognition should be performed in a knowledge domain—a domain of interest such as radiology, pathology, or tort law. This adds additional complexity to building semantic rules. The method described achieves semantic understanding by coupling a speech recognition engine to a semantic recognizer, which draws from a database of domain sentences derived from a document corpus, and a knowledge base created for these domain sentences. The method is able to identify in near real-time the best sentence hypotheses from the speech recognizer and its associated meanings, i.e. propositions, which belong to the knowledge domain, and if no hypotheses are found mark it as invalid for easy identification. For invalid sentences, closely matched sentences from the domain database can be displayed to speed correction. The semantic propositions can be semantically typed, such as normal and abnormal, further aiding in the identification of recognition errors. The system automatically displays the semantic meaning of related ideas of valid sentences by retrieving proposition (s) from the knowledge base.

The present invention is based on the use of annotation. An annotation is an information that can be applied to a content to provide extra information.The present invention provides for a method and system to use an annotation being imported into a document to replicate the ontology related to this annotation and to exploits this replication to create indirect links between different ontologies elements. The indirect links between the different ontologies constitute by themselves a global ontology that can be used by search engines to locate web contents in the Semantic Web.

Semantic Web attributes are transmitted via an electronic message such as an email message. The attributes are extracted from the message by a program agent according to a predetermined plan. The extracted attributes are saved in storage wherein the storage is optionally an annotation store.

The present invention relates to a system and method for intelligent ontology based knowledge search engine (IATOPIA KnowledgeSeeker). Said IATOPIA KnowledgeSeeker, is an intelligent ontology-based system that is designed to help Web users to find, retrieve, and analyze any Web information such as news articles from the Internet and then present the content in a semantic web. We present the benefits of using ontologies to analyze the semantics of Chinese text, and also the advantages of using a semantic web to organize information semantically. IATOPIA KnowledgeSeeker also demonstrates the advantages of using ontologies to identify topics. We use a Chinese document corpus to evaluate IATOPIA KnowledgeSeeker and the testing result was compared to other approaches. It was found that the accuracy of identifying the topics of Chinese web articles is over 87%. It demonstrated a fast processing speed of less than one second per article. It also organizes content flexibly and understands knowledge accurately, unlike traditional text classification systems used in popular search engines today such as Google and Yahoo.

A computer implemented method of constructing a computer implemented knowledge base, of evaluating a plurality of invoices, of knowledge refinement and generation, as well as a computer implemented knowledge base for analyzing a plurality of invoices. The methods comprise receiving the invoices, semantic and logically analyzing them to identify the invoice items (parameters and algorithms of service providers, billing plans, user profile, consumption pattern and debits) and relations connecting them and construct the knowledge base. The knowledge base comprises a hierarchic taxonomy of billing plans related to services of any domain (telecommunications services, banking, insurance, utilities etc.) and a computer implemented generic invoice constructed in reverse engineering logic for simulating debits. Debit simulations are done in order to achieve: 1. recommendations for optimal billing plans. 2. Recommendations for possible detected billing errors. 3. recommendations concerning new plans and / or services, and their financial implications Improving the knowledge base may use genetic algorithms based on an analogous hierarchic structure of the taxonomy to a genetic hierarchy, and may proceed by refining billing plans and comparing the resulting debits. Novel Semantic-web and Artificial Intelligence (AI) methods are used.

A hybrid approach for capturing meta data about Business Processing Monitoring (BPM) artifacts is based on a combination of a relational meta data model and a semantic net. Meta data about metrics and situations and their dimensional context are first captured. Then, relational meta data are used to describe a generic data schema for metrics, situations and their dimensional context. The meta data from semantic nets are used to extend the meta data definitions. Data from a data warehouse are searched and managed with the schema described and managed with the relational and semantic net meta data.

A semantic query over an RDF database is received with RDF database statistics and access methods for evaluating triple patterns in the query. The semantic query is expressed as a parse tree containing triple patterns and logical relationships among the triple patterns. The parse tree and access methods create a data flow graph containing a plurality of triple pattern and access method pair nodes connected by a plurality of edges, and an optimal flow tree through the data flow graph is determined such that costs are minimized and all triple patterns in the semantic query are contained in the optimal flow tree. A structure independent execution tree defining a sequence of evaluation through the optimal flow tree is created and is transformed into a database structure dependent query plan. This is used to create an SQL query that is used to evaluate the semantic query over the RDF database.

A configuration-file generation system for generating a configuration-file to configure an application for an enterprise is provided. The configuration-file generation system includes an IVR module for enabling a user to verbally interact with the configuration-file generation system. The configuration-file generation system further includes an analyzing module for analyzing and querying any information missed by the user. The configuration-file generation system further includes a suggestion module for searching and suggesting possible options corresponding to the missing information with the help of semantic web technology and with an experience database. The configuration-file generation system further includes a configuration-file generation module for generating a configuration-file based on available information received from the user. The configuration-file may then be passed to an application configuration module for configuring the application as required.

Ontology alignment is achieved using an exchange of annotations between different actors (users, software agent, application, etc.) over the Internet in order to create aligned ontologies that can be used by search engines to locate web content in the Semantic Web. An annotation related to a source ontology is received from a different storage medium. The ontology associated with that annotation is retrieved in order to make a local copy. The copied ontology is renamed before its content can be modified through a user interface. Every element modified inside the copied ontology is then automatically tagged with information in that links the modified element to the corresponding element in the source ontology. Alignment between the copied ontology and the source ontology is thereby achieved.

In future large-scale Emergency Response / Management (ER / EM) to terrorism and natural disasters, sharing the so-called common operational picture amongst dynamic task groups provides immediate advantages. In an ER / EM scenario, dissemination of the right data to the right person at the right time has a direct benefit. Timely and bandwidth efficient dissemination of sensor and Command and Control data remains a challenge. For example, dynamically changing mobile teams, information-needs profiling, information routing based upon information needs (not on IP address) are all complex issues. Accordingly, a protocol, called dissemination mesh, for constructing and reconfiguring network paths for disseminating information from sources to sinks, a software architecture for multi-domain wireless network information dissemination in the context of emergency response (resting above existing MANET protocols), supports needs-based dissemination, node mobility, rapidly changing groups (information sinks) and sensor networks (sources) is provided. The protocol includes: exploitation of Semantic Web and collaborative agent technologies, novel subscription-based information dissemination, intelligent networked information intermediaries, smart dissemination mesh forming and management. Together these technologies provide information dissemination management in the wireless setting. Application realms other than ER / EM can also be supported.

The inventive embodiment discloses an indexing system based on a semantic body. The system comprises a semantic body index database and a semantic body indexing processing unit. The semantic body indexing processing unit is used for acquiring a text hit file list, matching the text hit file list with a semantic body index in the semantic body index database to obtain a file semantic classification list. The indexing system can identify the semantic information of a file to be indexed, and the semantic classification result is presented in the searching result. The invention also discloses an indexing method based on semantic body, which comprises constructing semantic body index for the file with constructed text index, and performing semantic body index matching to the text matching result when user is searching, so that the semantic classification is presented in the final output result based on the conventional text matching result, thereby facilitating user's searching.

Disclosed is a process for ranking semantic web resources, comprising the steps of; establishing an RDF knowledge base using diverse tools that support the establishment of ontologies; setting, by class, object and subject weights for an object type attribute and a weight for a data type attribute on the schema composed of classes that constitute a domain and of attributes that describe relationships between these classes; extracting from the RDF knowledge base an RDF triple composed of three portions, i.e., a subject, a predicate and an object; creating a weight matrix of class-oriented attributes based on a set weight and the extracted RDF triple; and operating the created weight matrix of class-oriented attributes to calculate a first eigenvector and obtain a vector for ranking scores of resources.

A data infrastructure for graph-based computing that combines the natural language expressiveness of the Semantic Web and the mathematical rigor of graph theory to discover meaningful associations across multiple sources towards computer-assisted serendipitous insight discovery. The process automatically integrates massive size datasets accessed using Semantic Web standards and technologies and normalizes data in graphs. The process generates a plurality of conditional probability distributions based on type-triple meta-data and triple statistics to model saliency and automatically construct and evaluate a plurality of sub-graphs based on the plurality of conditional probabilities for contextual-saliency. The process then renders a plurality of paths (i.e. sequence of associations) that model meaningful pairwise relations between objects of the normalized integrated data. The pluralities of conditional probabilities reveal and rank previously unknown associations between entities of user-interest in the knowledge graph.

Embodiments of the present invention relate to a data processing system comprising a receiver to receive a first entity comprising first meta-data, expressed using a semantic web language, defining at least one relationship between first software and at least one associated patch for the first software; means to receive a second entity comprising second meta-data, expressed using the semantic web language, defining at least one relationship between installed software and at least one installed patch for the installed software; and a semantic web query language engine for subjecting the one or more of the first meta-data, second meta-data and an ontology, expressing concepts and relationships between software and at least one patch for said software, to an analysis; and means to output data representing the result of the analysis; the result providing data relating to at least one of the first meta-data and the second meta-data.

A computer implemented method, system and computer program product for managing reusable software assets based on software requirements. A topic map can be expressed utilizing semantic web technology in order to model a relationship between a software requirement and a reusable software asset. The relationship includes the software assets needed to satisfy the software requirement, relationship between the software assets, and the location of the software assets. The semantic web representation can then leverage a standard web based query mechanism to allow meaningful queries to suggest best software assets to be utilized with the software requirement. The semantic web representation can also leverage standard XML (extensible markup language) tooling to provide consistence checking and inferencing of new data.

Selecting and downloading a necessary part of an ontology from an ontology server in a semantic web technology. An ontology server according to the invention comprises an ontology storing section for storing a file of an ontology described in an ontology description language, and an ontology editing section for reading the ontology from the ontology storing section, extracting a given part from the read ontology, and transmitting it to an ontology client. The ontology server transmits a subset extracted from the ontology to the ontology client in response to a request from the ontology client.

To enable a user to perform, by using an ontology, an information search utilizing a meaning given to information on a network by Semantic Web without being required to perform complicated operations for forming an inquiry sentence in conformity with the ontology. In a stage before a search engine for performing an information search by using an ontology is provided an information search supporting system having a morpheme analysis section, a syntactic and semantic analysis section, and a conversion execution section which converts a natural language sentence on which syntactic analysis and semantic analysis have been performed into an inquiry sentence described in an ontology description language by referring to a case frame ontology dictionary in which are stored information indicating to which property in an ontology does the relationship among a predicate, a subject and an object in the natural language sentence correspond and the case frame of the natural language sentence in the property. A natural language sentence is input and an inquiry sentence described in the ontology language is formed on the basis of the results of syntactic analysis and semantic analysis on the natural language sentence and is provided to the search engine.

Database management systems and methods for managing a database are disclosed. In one embodiment, a database management system is provided that comprises a database layer including a database for storing data, and a spreadsheet layer for representing data from the database layer in a spreadsheet in accordance with a view, wherein the view causes at least one of a delivery of data to the spreadsheet layer from the database layer and a maintenance of data from the spreadsheet layer to the database layer. The system may further comprise an interface layer arranged to interface the database layer with the spreadsheet layer, wherein the database layer stores in the database data corresponding to a plurality of entities of a plurality of entity types in a plurality of tables, respectively, wherein the plurality of entities are linked by a plurality of relations in a predetermined structure, and further wherein the interface layer comprises a semantic net server for transforming the structure of the data in the database layer into a semantic net and the view is defined in terms of the semantic net to facilitate an interoperability between the database layer and the spreadsheet layer.

The invention provides a case knowledge base representation and case similarity obtaining method. The case knowledge base expression and case similarity obtaining method comprises the steps of improving semantic representation capacity of semantic web standard description languages, establishing a case knowledge base and obtaining case similarity, wherein the step of improving the semantic representation capacity of semantic web standard description languages is that an N-element relation model, a fuzzy membership function and relation weight are introduced on the basis of semantic web standard description languages to improve the semantic representation capacity of the semantic web standard description languages; establishing a case knowledge base based on the strengthened semantic web standard description languages, wherein the case knowledge base include case knowledge representation models, the case base, a semantic web ruler base and an inference mechanism based on the semantic web standard description languages; obtaining case similarity. By means of the case knowledge base representation and case similarity obtaining method, the semantic representation capacity of the semantic web standard description languages can be improved so as to accurately represent case knowledge, facilitate case knowledge management and share and improve case recommendation speed and recommendation accuracy.

A method for indexing and obtaining information of semantic network includes setting up inverted table used for indexing entity and file of semantic network and adding concrete content in two said inverted tables separately, indexing relevant inverted table separately according to different types of requests to obtain intermediate result set, sequencing intermediate result set requiring to be sequenced and updating sample requiring to update operation.

Propagating information in a computer network, in one aspect, may include detecting an online action performed by a user on a content presented on a computer. The content may be annotated with an identifier. A semantic graph may be searched for a semantic node representing the identifier. The semantic graph may be searched for one or more other semantic nodes representing one or more other identifiers that meet a semantic similarity threshold based on weighted distances between the semantic node and the one or more other semantic nodes. One or more other users represented in a social graph may be determined that have interest in one or more topics represented by the identifier and the one or more other identifiers. The online action on the content may be propagated to the one or more other users.