Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  present a new approach that incorporates semantic information from a document, in the form of Hierarchical Document Signature (HDS), to measure semantic similarity beten sentences. Due to variability of expressions of natural language, it is very essential to exploit the semantic properties of a document to accurately identify semantically similar sentences since sentences conveying the same fact or concept may be composed lexically and syntactically different. Inversely, sentences which are lexically common may not necessarily convey the same meaning. This poses a significant impact on many text mining applications performance where sentence-level judgment is involved. Our HDS uses the natural hierarchy of the document and represents it in a modularized form of document level to sentence level, sentence to word level; aggregating similarity components at the lor levels and propagating them to the next higher level to produce the final similarity beten sentences. The evaluation of our HDS model has shown that it resembles the decision making process as done by human to a greater extent than different vector space models which only uses ‘bag of words’ concept.
['Sukanya Manna', 'Tamás D. Gedeon']
I am writing a research paper on a idea Semantic Hierarchical Document Signature for determining sentence similarity
[{"from": "human", "value": "I am writing a research paper on a idea Semantic Hierarchical Document Signature for determining sentence similarity"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  present a new approach that incorporates semantic information from a document, in the form of Hierarchical Document Signature (HDS), to measure semantic similarity beten sentences. Due to variability of expressions of natural language, it is very essential to exploit the semantic properties of a document to accurately identify semantically similar sentences since sentences conveying the same fact or concept may be composed lexically and syntactically different. Inversely, sentences which are lexically common may not necessarily convey the same meaning. This poses a significant impact on many text mining applications performance where sentence-level judgment is involved. Our HDS uses the natural hierarchy of the document and represents it in a modularized form of document level to sentence level, sentence to word level; aggregating similarity components at the lor levels and propagating them to the next higher level to produce the final similarity beten sentences. The evaluation of our HDS model has shown that it resembles the decision making process as done by human to a greater extent than different vector space models which only uses \u2018bag of words\u2019 concept."}]