Abstract: System and methods are disclosed for determining the connotation or sentiment type of a text unit comprising multiple terms and with a grammatical structure, such as subject+verb, verb+object, adjective+noun, noun+noun, noun+preposition+noun. The connotation or sentiment type of the text unit is determined by applying context rules where the context of the grammatical structure may change the inherent or default connotations of individual terms in the text unit. The methods provide a solution to the challenge of correctly or accurately determining the sentiment type of various linguistic structures under different context, and to the simplistic approach of using the inherent or default connotation of individual terms for the linguistic structure containing such terms.

Abstract: System, methods, and user interface for managing emails and other message communications are disclosed as solutions for reducing confusion and avoiding mistakes in communications when replying to a message with multiple recipients. The mode of replying either to the sender only or to multiple recipients is first detected, and notifications and user interface objects are displayed to help the user to make sure the message is sent to the intended recipient, and to easily correct a mistake and switch the mode of reply for enhanced productivity. The notification can be displayed based on the user actions or based on the results of a text analysis of the content of the message.

Abstract: A computer system and methods are disclosed for automatically discovering topics and building a hierarchical topic structure, and for tagging and categorizing contents in a document or other natural language contents. The disclosed methods include steps for obtaining terms that best represent the topics in a text content, and building a hierarchical representation of topics of different levels or topic-comment relationships, and folder-subfolder structures. The methods further include obtaining, identifying, and selecting terms representing different degrees of informational importance based on the grammatical roles, parts of speech, and semantic attributes associated with the terms, using the terms to represent topics in the document, to automatically tag the document, to rank search results, and to build a category structure based on the selected terms.

Abstract: A system and methods and data structure for quantitatively assessing associations between terms or symbols in natural language and non-natural language contents. Some of the terms represent objects or concepts or semantic attributes; some other terms represent properties associated with the objects or concepts or attributes. The methods include obtaining a first group of text contents, specifying a target term or symbol, and identifying contextual attributes of the target term or symbol. The contextual attributes include grammatical and semantic attributes as well as positional and distance attributes. Association strength values are calculated for related terms or symbols based on the contextual attributes of the target term or symbol, and terms or symbols are selected to represent the properties of an object or concept or attribute.

Abstract: A system, methods and user interface are disclosed for determining the connotation or sentiment type of a text unit comprising multiple terms and with a grammatical structure, such as subject+verb, verb+object, adjective+noun, noun+noun, noun+preposition+noun, and for highlighting or extracting such text units. The connotation or sentiment type of the text unit is determined by applying context rules where the context of the grammatical structure may change the inherent or default connotations of individual terms in the text unit. The methods provide a solution to the challenge of correctly or accurately determining the sentiment type of various linguistic structures under different context, and to the simplistic approach of using the inherent connotation of individual terms for the linguistic structure containing such terms, and highlighting only such terms without considering the contextual effects.

Abstract: System and methods are disclosed for determining the connotation or sentiment type of a text unit comprising multiple terms and with a grammatical structure, such as subject+verb, verb+object, adjective+noun, noun+noun, noun+preposition+noun. The connotation or sentiment type of the text unit is determined by applying context rules where the context of the grammatical structure may change the inherent or default connotations of individual terms in the text unit. The methods provide a solution to the challenge of correctly or accurately determining the sentiment type of various linguistic structures under different context, and to the simplistic approach of using the inherent connotation of individual terms for the linguistic structure containing such terms.

Abstract: A system with methods and user interface for discovering and presenting information in text content with different view formats, including steps of identifying the grammatical, semantic, contextual, and topical attributes of the words or phrases in the text content, and providing user interface objects to allow the user to specify an attribute of the words or phrases in the content and perform an action on the words or phrases. The supported actions include extracting, displaying in a specific format, showing or hiding, or highlighting the words or phrases.

Abstract: System and methods are disclosed for determining the connotation or sentiment type of a text unit comprising multiple terms and with a grammatical structure, such as subject+verb, verb+object, adjective+noun, noun+noun, noun+preposition+noun. The connotation or sentiment type of the text unit is determined by applying context rules where the context of the grammatical structure may change the inherent or default connotations of individual terms in the text unit. The methods provide a solution to the challenge of correctly or accurately determining the sentiment type of various linguistic structures under different context, and to the simplistic approach of using the inherent or default connotation of individual terms for the linguistic structure containing such terms.

Abstract: System and methods are disclosed for advertising based on user intention detection. The methods include performing linguistic analysis of user expressions, identifying grammatical or semantic attributes associated with terms in the expression, and their relationships, and determining a relevance score for one or more terms in the expression that are associated with the name of a product or service. Based on the relevance score, an advertisement can be displayed to the user who produced the expression within a given period of time. The user can be a social network user, or an email user, or a text messaging user, or a user of other text communication media. Furthermore, electronic advertising space or time can be sold or auctioned to advertisers based on the relevance score in contrast to the conventional method of being based on keywords.

Abstract: Systems and methods are disclosed for presenting information related to an object including a word or phrase in a text content that is considered as unstructured data. Methods include identifying a term in the text content as a candidate for presenting such information. Once the term is identified, various data sources including document or email search indexes and relational or non-relational databases are searched, and data units related to the selected terms are retrieved and displayed in a user interface with a concurrent view of both the text content containing the term and the related information. Other methods for utilizing various visual effects to concurrently display relevant information associated with various user interface objects are also disclosed.