Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Desktop search is an important part of personal information management (PIM). Hover, research in this area has been limited by the lack of shareable test collections, making cumulative progress difficult. ,  define desktop search as a semi-structured document retrieval problem and introduce a methodology to automatically build a reusable collection (the pseudo-desktop) that has many of the same properties as a real desktop collection.  then present a comprehensive evaluation of retrieval methods for semi-structured document retrieval on several pseudo-desktop collections and the TREC Enterprise collection. Our results show that a probabilistic retrieval model using the mapping relation beten a query term and a document field (PRM-S) has the best performance in collections with more structure, such as email, and that the query-likelihood language model is better for other document types.  further analyze the observed differences using generated queries and suggest ways to improve PRM-S, which makes the performance gains more significant and consistent.
['Jinyoung Kim', 'W. Bruce Croft']
I am writing a research paper on a idea Retrieval experiments using pseudo-desktop collections
[{"from": "human", "value": "I am writing a research paper on a idea Retrieval experiments using pseudo-desktop collections"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Desktop search is an important part of personal information management (PIM). Hover, research in this area has been limited by the lack of shareable test collections, making cumulative progress difficult. ,  define desktop search as a semi-structured document retrieval problem and introduce a methodology to automatically build a reusable collection (the pseudo-desktop) that has many of the same properties as a real desktop collection.  then present a comprehensive evaluation of retrieval methods for semi-structured document retrieval on several pseudo-desktop collections and the TREC Enterprise collection. Our results show that a probabilistic retrieval model using the mapping relation beten a query term and a document field (PRM-S) has the best performance in collections with more structure, such as email, and that the query-likelihood language model is better for other document types.  further analyze the observed differences using generated queries and suggest ways to improve PRM-S, which makes the performance gains more significant and consistent."}]