Abstract: A method, computer-readable medium, and a computer system for processing data are disclosed. First data associated with a search may be accessed. Second data may be accessed from a database using the first data, where the second data may be associated with at least one sentiment of the first data. The second data may include at least one score, at least one classification, and at least one degree, some combination thereof, etc. Third data may be generated, based on the second data, for performing at least one operation associated with the search results. The at least one operation may include filtering the search results, ranking the search results, displaying an image associated with the at least one sentiment, some combination thereof, etc.

Abstract: A method, computer-readable medium, and a computer system for automatically generating sentiment data are disclosed. One or more portions of at least one document may be determined to be associated with at least one sentiment of one or more other portions of the at least one document. One or more scores associated with the at least one sentiment may be automatically determined based on at least one respective attribute of the one or more portions. The at least one respective attribute may include a positive category, a negative category, a neutral category, a degree associated with a positive sentiment, a degree associated with a negative sentiment, some combination thereof, etc. In this manner, data associated with sentiment of one or more portions of at least one document may be generated.

Abstract: A method, computer-readable medium, and system for automatic generation of a search query are disclosed. A semantic key may be automatically recognized in a first search query, thereby allowing a second search query to be automatically generated based on the first search query. A first search may be performed using the second search query. Search results generated responsive to the first search may include one or more instances of at least one semantic sub-key associated with the semantic key. In this manner, more relevant search results may be returned while relieving the user of manually entering the semantic key separately from the search query keywords and/or demarcating the semantic key and the search query keywords.

Abstract: A computer-implemented method, computer-readable medium and system for scoring a text are disclosed. Themes within one or more texts may be determined and used to score each text, where an overall score for each text may indicate a respective importance and/or value of each text. The score for each text may be determined based upon a number of themes, type of themes, frequency of theme elements associated with the themes, distribution of theme elements associated with the themes, location of themes in the text, some combination thereof, etc. In this manner, the importance or value of one or more texts may be determined more accurately using information within each text with reduced reliance upon external information. Additionally, more relevant search results can be returned to a user by using internal information to perform ranking operations and/or filtering operations associated with a search.

Abstract: A method, computer-usable medium, and a computer system for searching for webpages are disclosed. Embodiments of the present invention provide a convenient and efficient mechanism for filtering results from a keyword search using semantic keys and semantic sub-keys, thereby enabling an increased number of irrelevant results to be filtered from a keyword search. The search query may be parsed to determine the focus of the query, where the focus may be used determine at least one semantic key for the search query. Each semantic key may be associated with at least one semantic sub-key, where the semantic keys and/or the semantic sub-keys may be used to filter the results of the keyword search. As such, broader keyword searches may be performed to include a larger number of relevant results, where the filtering mechanisms of the present invention may then filter an increased number of irrelevant results.

Abstract: A computer-implemented method, computer-readable medium and system for scoring a text are disclosed. Themes within one or more texts may be determined and used to score each text, where an overall score for each text may indicate a respective importance and/or value of each text. The score for each text may be determined based upon a number of themes, type of themes, frequency of theme elements associated with the themes, distribution of theme elements associated with the themes, location of themes in the text, some combination thereof, etc. In this manner, the importance or value of one or more texts may be determined more accurately using information within each text with reduced reliance upon external information. Additionally, more relevant search results can be returned to a user by using internal information to perform ranking operations and/or filtering operations associated with a search.

Abstract: A method, computer-readable medium, and a computer system for determining an ordering is disclosed. A search query including a semantic key and a superlative adjective may be accessed, where the semantic key may be associated with a plurality of semantic sub-keys. At least one respective instance of at least one respective superlative adjective in at least one respective document may be determined for each semantic sub-key of the plurality of semantic sub-keys. Each instance of the at least one respective instance may include a respective superlative adjective that is associated with a respective sentiment of a respective semantic sub-key of the plurality of semantic sub-keys. An ordering of the plurality of semantic sub-keys may be determined based on the at least one respective instance of at least one respective superlative adjective in at least one respective document.

Abstract: A method, computer-readable medium, and a computer system for automatically generating sentiment data are disclosed. One or more portions of at least one document may be determined to be associated with at least one sentiment of one or more other portions of the at least one document. One or more scores associated with the at least one sentiment may be automatically determined based on at least one respective attribute of the one or more portions. The at least one respective attribute may include a positive category, a negative category, a neutral category, a degree associated with a positive sentiment, a degree associated with a negative sentiment, some combination thereof, etc. In this manner, data associated with sentiment of one or more portions of at least one document may be generated.

Abstract: A method, computer-readable medium, and a computer system for processing data are disclosed. First data associated with a search may be accessed. Second data may be accessed from a database using the first data, where the second data may be associated with at least one sentiment of the first data. The second data may include at least one score, at least one classification, and at least one degree, some combination thereof, etc. Third data may be generated, based on the second data, for performing at least one operation associated with the search results. The at least one operation may include filtering the search results, ranking the search results, displaying an image associated with the at least one sentiment, some combination thereof, etc.

Abstract: A method, computer-readable medium, and system for ranking data are disclosed. Where a semantic key is associated with a search query, a plurality of semantic sub-keys associated with the semantic key may be determined. Each semantic sub-key of the plurality of semantic sub-keys may be associated with at least one respective attribute. At least one semantic sub-key of the plurality of semantic sub-keys may be determined, where the at least one semantic sub-key is associated with an attribute matching a portion of the search query. At least one document associated with the at least one semantic sub-key may be ranked above at least one other document associated with at least one other semantic sub-key of the plurality of semantic sub-keys. As such, ranking of documents associated with search results may be improved by utilizing attributes of semantic sub-keys.

Abstract: A method, computer-readable medium, and system for automatic generation of a search query are disclosed. A semantic key may be automatically recognized in a first search query, thereby allowing a second search query to be automatically generated based on the first search query. A first search may be performed using the second search query. Search results generated responsive to the first search may include one or more instances of at least one semantic sub-key associated with the semantic key. In this manner, more relevant search results may be returned while relieving the user of manually entering the semantic key separately from the search query keywords and/or demarcating the semantic key and the search query keywords.

Abstract: A method, computer-readable medium, and system for ordering data are disclosed. It may be automatically determined that a search query includes multiple semantic keys, where each semantic key of the multiple semantic keys is associated with a respective set of semantic sub-keys of a plurality of sets of semantic sub-keys. A sort key may be automatically determined based on an analysis of the plurality of sets of semantic sub-keys. An ordering of the semantic sub-keys may be automatically determined based on the sort key. As such, where the ordering of semantic sub-keys is output for presentation, the information may be presented in a manner that is easier to understand and interact with.

Abstract: A method, computer-readable medium, and system for ranking data are disclosed. It may be automatically determined that a search query includes multiple semantic keys. Respective sets of semantic sub-keys may be determined for each of the multiple semantic keys. Documents including at least one instance of a semantic sub-key associated with the multiple semantic keys may be ranked above documents which do not include at least one instance of a semantic sub-key associated with the multiple semantic keys. In this manner, ranking of documents associated with search results may be improved by utilizing semantic sub-keys associated with multiple semantic keys included in the search query.

Abstract: A method, computer-readable medium, and a computer system for performing a search are disclosed. Embodiments of the present invention provide a convenient and efficient mechanism for performing a search based on search data, where the search data may include a search query and at least one semantic key. The semantic key may be used to determine at least one document. Results from the search may be filtered using the at least one document. In this manner, more relevant search results may be returned.

Abstract: A computer-implemented method, computer-readable medium and system for scoring a text are disclosed. Themes within one or more texts may be determined and used to score each text, where an overall score for each text may indicate a respective importance and/or value of each text. The score for each text may be determined based upon a number of themes, type of themes, frequency of theme elements associated with the themes, distribution of theme elements associated with the themes, location of themes in the text, some combination thereof, etc. In this manner, the importance or value of one or more texts may be determined more accurately using information within each text with reduced reliance upon external information. Additionally, more relevant search results can be returned to a user by using internal information to perform ranking operations and/or filtering operations associated with a search.

Abstract: A method, computer-usable medium, and a computer system for searching for webpages are disclosed. Embodiments of the present invention provide a convenient and efficient mechanism for filtering results from a keyword search using semantic keys and semantic sub-keys, thereby enabling an increased number of irrelevant results to be filtered from a keyword search. The search query may be parsed to determine the focus of the query, where the focus may be used determine at least one semantic key for the search query. Each semantic key may be associated with at least one semantic sub-key, where the semantic keys and/or the semantic sub-keys may be used to filter the results of the keyword search. As such, broader keyword searches may be performed to include a larger number of relevant results, where the filtering mechanisms of the present invention may then filter an increased number of irrelevant results.