Abstract: A new information in a language and relating to a subject matter domain is parsed into a constituent set of complete grammatical constructs. In a subset of the complete grammatical constructs, a set of linguistic styles of the language is identified according to a subset of a set of word-style associations related to the language and independent of the subject matter domain. A first weight is assigned to a first linguistic style and a second weight to a second linguistic style from the set of linguistic styles. A first intention information is mapped to the first style using a first style-intention rule, and a second intention information to the second style using a second style-intention rule. A complete grammatical construct in the subset is tagged with the first intention information responsive to a weight associated with the first intention information exceeding an intention selection threshold.

Abstract: A new information in a language and relating to a subject matter domain is parsed into a constituent set of complete grammatical constructs. In a subset of the complete grammatical constructs, a set of linguistic styles of the language is identified according to a subset of a set of word-style associations related to the language and independent of the subject matter domain. A first weight is assigned to a first linguistic style and a second weight to a second linguistic style from the set of linguistic styles. A first intention information is mapped to the first style using a first style-intention rule, and a second intention information to the second style using a second style-intention rule. A complete grammatical construct in the subset is tagged with the first intention information responsive to a weight associated with the first intention information exceeding an intention selection threshold.

Abstract: A named entity input is received and a target sense for which the named entity input is to be extracted from a set of documents is identified. An extraction complexity feature is generated based on the named entity input, the target sense, and the set of documents. The extraction complexity feature indicates how difficult or complex it is deemed to be to identify the named entity input for the target sense in the set of documents.

Abstract: Embodiments of the present invention relate to scoring of messages published to digital media based on past performance of similar messages. In one embodiment, an input token is received. A plurality of messages is selected from a corpus of messages. Each of the plurality of messages has a publication time and contents. The contents of each of the plurality of messages include the input token. A plurality of root messages is determined from the plurality of messages. Each of the plurality of root messages relates to at least one related message. The at least one related message is one of the plurality of messages. Each of the plurality of root messages is the earliest message of the corpus of messages related to its at least one related message. A score is determined for the input token based on the plurality of root messages.

Abstract: Embodiments of the present invention relate to interactive optimization of messages published to digital media based on past performance of similar messages. In one embodiment, an input token is received. At least one candidate substitute token is retrieved from a dictionary. The dictionary comprises a mapping from the input token to the at least one candidate substitute token. A score associated with the at least one candidate substitute token is determined. A score associated with the input token is determined. The score associated with the input token, the at least one candidate substitute token, and the score associated with the at least one candidate substitute token are outputted.

Abstract: The present invention generally relates to methods and systems for analysis of real-time user-generated text messages. The methods and systems allow analysis to be performed using term associations and geographical and temporal constraints.

Abstract: A named entity input is received and a target sense for which the named entity input is to be extracted from a set of documents is identified. An extraction complexity feature is generated based on the named entity input, the target sense, and the set of documents. The extraction complexity feature indicates how difficult or complex it is deemed to be to identify the named entity input for the target sense in the set of documents.

Abstract: A named entity input is received and a target sense for which the named entity input is to be extracted from a set of documents is identified. An extraction complexity feature is generated based on the named entity input, the target sense, and the set of documents. The extraction complexity feature indicates how difficult or complex it is deemed to be to identify the named entity input for the target sense in the set of documents.

Abstract: The present invention generally relates to methods and systems for analysis of real-time user-generated text messages. The methods and systems allow analysis to be performed using term associations and geographical and temporal constraints.

Abstract: A named entity input is received and a target sense for which the named entity input is to be extracted from a set of documents is identified. An extraction complexity feature is generated based on the named entity input, the target sense, and the set of documents. The extraction complexity feature indicates how difficult or complex it is deemed to be to identify the named entity input for the target sense in the set of documents.