Abstract: Method, system, and programs for information search and retrieval. A query is received and is processed to generate a feature-based vector that characterizes the query. A unified representation is then created based on the feature-based vector, that integrates semantic and feature based characterizations of the query. Information relevant to the query is then retrieved from an information archive based on the unified representation of the query. A query response is generated based on the retrieved information relevant to the query and is then transmitted to respond to the query.

Abstract: Method, system, and programs for an information model to be used in representing data. The information model includes a plurality of features, one or more information allocation models, and a configuration that associates an information allocation model with each of the features, where an information allocation model is to be used to allocate a portion of information contained in the data to each of the features and the total amount of information allocated to the features equals a total amount of information contained in the data.

Abstract: Method, system, and programs for an information model to be used in representing data. The information model includes a plurality of features, one or more information allocation models, and a configuration that associates an information allocation model with each of the features, where an information allocation model is to be used to allocate a portion of information contained in the data to each of the features and the total amount of information allocated to the features equals a total amount of information contained in the data.

Abstract: Method, system, and programs for information search and retrieval. A query is received and is processed to generate a feature-based vector that characterizes the query. A unified representation is then created based on the feature-based vector, that integrates semantic and feature based characterizations of the query. Information relevant to the query is then retrieved from an information archive based on the unified representation of the query. A query response is generated based on the retrieved information relevant to the query and is then transmitted to respond to the query.

Abstract: An advertisement placement method and system for relating an advertisement to a dataset based on a trainable semantic vector (TSV) associated with the dataset and respective semantic representations of the advertisements. The trainable semantic vector associated with the dataset is generated based on at least one data point included in the dataset and known relationships between predetermined data points and predetermined categories. A comparison process is performed to determine a similarity between the trainable semantic vector associated with the dataset and the semantic representation associated with each of the plurality of advertisements. The system selectively relates one or more of the advertisements with the dataset based on a result of the comparison process. The selected advertisement or advertisements may be displayed with the dataset.

Abstract: Techniques for controlling distribution of information from a secure domain by automatically detecting outgoing messages which violate security policies corresponding to the secure domain. Semantic models are constructed for one or more message categories and for the outgoing messages. The semantic model of an outgoing message is compared with the semantic models of the message categories to determine a degree of similarity between the semantic models. The outgoing message is classified based on the degree of similarity obtained from the comparison. A determination is made, based on the classification of the outgoing message, if distribution of the outgoing message would violate a security policy for the secure domain. Distribution of the outgoing message is allowed if no security policy is violated.

Abstract: A system for retrieving multimedia information is provided using a computer coupled to a computer-based network, such as the Internet, and particularly the World Wide Web (WWW). The system includes a web browser, a graphic user interface enabled through the web browser to allow a user to input a query representing the information the user wishes to retrieve, and an agent server for producing, training, and evolving first agents and second agents. Each of the first agents retrieves documents (Web page) from the network at a different first network address and at other addresses linked from the document at the first network address. Each of the second agents executes a search on different search engines on the network in accordance with the query to retrieve documents at network addresses provided by the search engine. The system includes a natural language processor which determines the subject categories and important terms of the query, and of the text of each agent retrieved document.

Abstract: A system and method for improving information retrieval effectiveness by dynamically combining evidence information produced by a plurality of retrieval systems matching alternative representations of queries and documents. The user enters a query and the system generates alternative representations of the query. The system also maintains a collection of documents and corresponding alternative representations of the documents. The system then performs matching between the alternative representations of the query and the corresponding alternative representations of the documents and generates individual matching scores for the alternative representation matches. Correlation information is also determined for the individual scores. The individual matching scores are combined using a dynamic combination regime which is adjusted for the query. The dynamic combination regime may be a function of query specific information, retrieved documents specific information, or correlation information.

Abstract: An information extraction system that allows users to ask questions about documents in a database, and responds to queries by returning possibly relevant information which is extracted from the documents. The system is domain-independent, and automatically builds its own subject knowledge base. It can be applied to any new corpus of text with quick results, and no requirement for lengthy manual input. For this reason, it is also a dynamic system which can acquire new knowledge and add it to the knowledge base immediately by automatically identifying new names, events, or concepts.

Abstract: Techniques for generating sophisticated representations of the contents of both queries and documents in a retrieval system by using natural language processing (NLP) techniques to represent, index, and retrieve texts at the multiple levels (e.g., the morphological, lexical, syntactic, semantic, discourse, and pragmatic levels) at which humans construe meaning in writing. The user enters a query and the system processes the query to generate an alternative representation, which includes conceptual-level abstraction and representations based on complex nominals (CNs), proper nouns (PNs), single terms, text structure, and logical make-up of the query, including mandatory terms. After processing the query, the system displays query information to the user, indicating the system's interpretation and representation of the content of the query. The user is then given an opportunity to provide input, in response to which the system modifies the alternative representation of the query.