Abstract: A method for detecting solutions to a problem using content in online discussion sources. The method includes receiving a request, such request identifying a problem, and searching multiple online discussion sources for content related to the problem. Responsive to finding content related to the problem, the method searches the multiple online discussion sources for a plurality of solutions to the problem. Responsive to finding a plurality of solutions to the problem, the method forms groups containing the solutions from each of the multiple online discussion sources. The method then determines a likeliness to solve the problem for each of the groups and ranks the groups based on the determined likeliness to solve the problem. The method then determines that the rank of at least one group meets a threshold value, wherein the threshold value is based on a confidence in the likeliness to solve the problem.

Abstract: Extracting and mining of quote data across multiple languages, including: retrieving, from a plurality of quote sources, a plurality of commentary summarizations, wherein each commentary summarization is embodied as a machine-readable data structure and wherein the plurality of commentary summarizations include information in at least two or more languages; for each commentary summarization: identifying, within the commentary summarization, quote data, wherein the quote data represents a quote from a commentator; creating a quote tuple for the quote data, the quote tuple including information associated with quantifiable aspects of the quote data; and storing, in a quote tuple repository, the quote tuple; mining, for quote analysis information, the quote tuple repository; and presenting, to a user, the quote analysis information.

Abstract: Extracting and mining of quote data across multiple languages, including: retrieving, from a plurality of quote sources, a plurality of commentary summarizations, wherein each commentary summarization is embodied as a machine-readable data structure and wherein the plurality of commentary summarizations include information in at least two or more languages; for each commentary summarization: identifying, within the commentary summarization, quote data, wherein the quote data represents a quote from a commentator; creating a quote tuple for the quote data, the quote tuple including information associated with quantifiable aspects of the quote data; and storing, in a quote tuple repository, the quote tuple; mining, for quote analysis information, the quote tuple repository; and presenting, to a user, the quote analysis information.

Abstract: Extracting and mining of quote data across multiple languages, including: retrieving, from a plurality of quote sources, a plurality of commentary summarizations, wherein each commentary summarization is embodied as a machine-readable data structure and wherein the plurality of commentary summarizations include information in at least two or more languages; for each commentary summarization: identifying, within the commentary summarization, quote data, wherein the quote data represents a quote from a commentator; creating a quote tuple for the quote data, the quote tuple including information associated with quantifiable aspects of the quote data; and storing, in a quote tuple repository, the quote tuple; mining, for quote analysis information, the quote tuple repository; and presenting, to a user, the quote analysis information.

Abstract: Extracting and mining of quote data across multiple languages, including: retrieving, from a plurality of quote sources, a plurality of commentary summarizations, wherein each commentary summarization is embodied as a machine-readable data structure and wherein the plurality of commentary summarizations include information in at least two or more languages; for each commentary summarization: identifying, within the commentary summarization, quote data, wherein the quote data represents a quote from a commentator; creating a quote tuple for the quote data, the quote tuple including information associated with quantifiable aspects of the quote data; and storing, in a quote tuple repository, the quote tuple; mining, for quote analysis information, the quote tuple repository; and presenting, to a user, the quote analysis information.

Abstract: A method for detecting solutions to a problem using content in online discussion sources. The method includes receiving a request, such request identifying a problem, and searching multiple online discussion sources for content related to the problem. Responsive to finding content related to the problem, the method searches the multiple online discussion sources for a plurality of solutions to the problem. Responsive to finding a plurality of solutions to the problem, the method forms groups containing the solutions from each of the multiple online discussion sources. The method then determines a likeliness to solve the problem for each of the groups and ranks the groups based on the determined likeliness to solve the problem. The method then determines that the rank of at least one group meets a threshold value, wherein the threshold value is based on a confidence in the likeliness to solve the problem.