Abstract: A system including a global topic model building module that builds a global topic model based on a set of data that is updated according to an activity of each user of a plurality of users, a user model building module that builds a plurality of user models, each user model being built based on an activity of a respective user, an expertise model building module that builds an expertise model for the topic based on the activity of at least one user of the plurality of users, the expertise model for the topic setting a target level of knowledge for a first user of the plurality of users, a processor to compare a user model of the first user with the expertise model for the topic; and an expertise assessment and learning recommendation module that recommends an activity associated with the set of data to the first user based on the comparison.

Abstract: A method including generating a global topic model based on a set of data that is updated according to an activity of each user of a plurality of users, the global topic model including a topic representation for a topic, generating a plurality of user models, each user model being generated based on the activity of a respective user, generating an expertise model for the topic based on the activity of at least one user of the plurality of users, the expertise model for the topic setting a target level of knowledge for a first user of the plurality of users, comparing a user model of the first user with the expertise model for the topic, the comparing being performed by a processor of a computer system, and recommending an activity associated with the set of data to the first user based on the comparison.

Abstract: A system including a global topic model building module that builds a global topic model based on a set of data that is updated according to an activity of each user of a plurality of users, a user model building module that builds a plurality of user models, each user model being built based on an activity of a respective user, an expertise model building module that builds an expertise model for the topic based on the activity of at least one user of the plurality of users, the expertise model for the topic setting a target level of knowledge for a first user of the plurality of users, a processor to compare a user model of the first user with the expertise model for the topic; and an expertise assessment and learning recommendation module that recommends an activity associated with the set of data to the first user based on the comparison.

Abstract: A method including generating a global topic model based on a set of data that is updated according to an activity of each user of a plurality of users, the global topic model including a topic representation for a topic, generating a plurality of user models, each user model being generated based on the activity of a respective user, generating an expertise model for the topic based on the activity of at least one user of the plurality of users, the expertise model for the topic setting a target level of knowledge for a first user of the plurality of users, comparing a user model of the first user with the expertise model for the topic, the comparing being performed by a processor of a computer system, and recommending an activity associated with the set of data to the first user based on the comparison.

Abstract: A method for capitalizing text in a document includes processing a reference corpus to construct a plurality of dictionaries of capitalized terms, where the plurality of dictionaries include a singleton dictionary and a phrase dictionary. Each record in the singleton dictionary contains a word in lowercase, a range of phrase lengths m:n for capitalized phrases that the word begins, where m is a minimum phrase length and n is a maximum phrase length, and where each record in the phrase dictionary includes a multi-word phrase in lowercase. The method adds proper capitalization to an input monocase document by capitalizing words found in mandatory capitalization positions; and by looking up each word in the singleton dictionary and, if the word is found in the singleton dictionary, testing the corresponding phrase length range.

Abstract: A system and method is disclosed for performing Automatic Stream Analysis for Broadcast Information which takes speech audio as input, converts the audio stream into text using a speech recognition system, applies a variety of analyzers to the text stream to identify information elements, automatically generates queries from these information elements, and extracts data from search results that is relevant to a current program. The data is multiplexed into the broadcast signal and transmitted along with the original audio/video program. The system is fully automatic and operates in real time, allowing broadcasters to add relevant collateral information to live programming.

Abstract: A method for capitalizing text in a document includes processing a reference corpus to construct a plurality of dictionaries of capitalized terms, where the plurality of dictionaries include a singleton dictionary and a phrase dictionary. Each record in the singleton dictionary contains a word in lowercase, a range of phrase lengths m:n for capitalized phrases that the word begins, where m is a minimum phrase length and n is a maximum phrase length, and where each record in the phrase dictionary includes a multi-word phrase in lowercase. The method adds proper capitalization to an input monocase document by capitalizing words found in mandatory capitalization positions; and by looking up each word in the singleton dictionary and, if the word is found in the singleton dictionary, testing the corresponding phrase length range.

Abstract: A query comprising of sub queries, each of which could be of different media types are used to search a collection of multimedia documents in a database. These sub queries are parsed according to media type and operators/functions between these sub queries are recorded creating a set of query objects and query operator objects. The query interface than passes the query objects to the appropriate application programming interfaces (API's) of the various search engines. Furthermore, it applies the query object operators to the respective interim results obtained by executing a query object. Then the interim results are combined in a global result object that is processed using a user specification to produce a single combined result list that conforms to user specified requirements.