Context-based key phrase discovery and similarity measurement utilizing search engine query logs

A method for facilitating key phrase processing, comprising:

• employing a processor operatively coupled to memory to execute the key phrase processing, comprising:
• obtaining data from at least one search query log;
• extracting key phrases from the search query log data;
• and
• breaking individual queries into key phrase vectors to provide query breakup information, the breakup information for each key phrase is based at least in part on a function of the frequency of each key phrase and the number of words in each key phrase;
• generating a key phrase Co-occurrence Graph utilizing the query breakup information;
• pruning edges with a weight less than a first threshold number from the Co-occurrence Graph;
• pruning nodes and the associated edges which have less than a second threshold number of edges from the Co-occurrence Graph;
• determining top K edges for each node of the Co-occurrence Graph, where K is an integer from one to infinity;
• removing edges from the Co-occurrence Graph except for the edges fall into the top K of at least one node;
• creating a Similarity Graph from remaining key phrase nodes of the Co-occurrence Graph;
• determining edges for the Similarity Graph;
• determining top E edges by edge weight for each node in the Similarity Graph, where L is an integer from one to infinity;
• and
• removing edges from the Similarity Graph except those that fall into the top E edges of at least one node;
• and
• outputting the Similarity Graph to facilitate applications that utilize similarities between key phrases.

A system that facilitates key phrase processing, comprising:

• means for obtaining data from at least one search query log;
• means for removing URL queries from search query log data;
• means for extracting key phrases from the filtered search query log data, the means for extracting key phrases being configured to:
• count frequencies of individual words that occur in the search query log data;
• and
• discard words with a frequency lower than a first pre-set threshold limit;
• generate possible phrases up to a pre-set length of n words for each search query, where n is an integer from one to infinity;
• and
• count frequencies of phrases and discarding infrequent phrases to create candidate key phrases;
• means for breaking each search query into key phrase vectors, the means for breaking each search query being configured to:
• estimate a best break for each search query;
• increment a real count of each constituent key phrase of a best break search query by one;
• and
• means for providing the query breakup information to facilitate in determining key phrase similarities.

A computer-executed method for facilitating key phrase processing by employing a processor to execute computer executable instructions stored on memory, comprising:

• obtaining data from at least one search query log;
• removing URL queries from the search query log data;
• extracting key phrases from the search query log data by:
• counting frequencies of individual words that occur in the search query log data;
• discarding words with a frequency lower than a first pre-set threshold limit;
• generating possible phrases up to a pre-set length of n words for each search query, where n is an integer from one to infinity and counting frequencies of phrases;
• and
• discarding infrequent phrases to create candidate key phrases;
• breaking individual queries into key phrase vectors to provide query breakup information by estimating a best break for each search query and incrementing a real count of each constituent key phrase of a best break search query by one;
• and
• providing the query breakup information to facilitate in determining key phrase similarities.