Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: There has been a great amount of work on query-independent summarization of documents. Hover, due to the success of b search engines  query-specific  document summarization (query result snippets) has become an important problem, which has received little attention.  present a method to create query-specific summaries by identifying the most query-relevant fragments and combining them using the semantic associations within the document. In particular,  first add structure to the documents in the preprocessing stage and convert them to  document graphs . Then, the best summaries are computed by calculating the top spanning trees on the document graphs.  present and experimentally evaluate efficient algorithms that support computing summaries in interactive time. Furthermore, the quality of our summarization method is compared to current approaches using a user survey.
['Ramakrishna Varadarajan', 'Vagelis Hristidis']
I am writing a research paper on a idea A system for query-specific document summarization
[{"from": "human", "value": "I am writing a research paper on a idea A system for query-specific document summarization"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: There has been a great amount of work on query-independent summarization of documents. Hover, due to the success of b search engines  query-specific  document summarization (query result snippets) has become an important problem, which has received little attention.  present a method to create query-specific summaries by identifying the most query-relevant fragments and combining them using the semantic associations within the document. In particular,  first add structure to the documents in the preprocessing stage and convert them to  document graphs . Then, the best summaries are computed by calculating the top spanning trees on the document graphs.  present and experimentally evaluate efficient algorithms that support computing summaries in interactive time. Furthermore, the quality of our summarization method is compared to current approaches using a user survey."}]