Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Morphology induction is a subproblem of important tasks like automatic learning of machine-readable dictionaries and grammar induction. Previous morphology induction approaches have relied solely on statistics of hypothesized stems and affixes to choose which affixes to consider legitimate. Relying on stem-and-affix statistics rather than semantic knowledge leads to a number of problems, such as the inappropriate use of valid affixes ("ally" stemming to "all").  introduce a semantic-based algorithm for learning morphology which only proposes affixes when the stem and stem-plus-affix are sufficiently similar semantically.  implement our approach using Latent Semantic Analysis and show that our semantics-only approach provides morphology induction results that rival a current state-of-the-art system.
['Patrick Schone', 'Daniel Jurafsky']
I am writing a research paper on a idea Knowledge-free induction of morphology using latent semantic analysis
[{"from": "human", "value": "I am writing a research paper on a idea Knowledge-free induction of morphology using latent semantic analysis"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Morphology induction is a subproblem of important tasks like automatic learning of machine-readable dictionaries and grammar induction. Previous morphology induction approaches have relied solely on statistics of hypothesized stems and affixes to choose which affixes to consider legitimate. Relying on stem-and-affix statistics rather than semantic knowledge leads to a number of problems, such as the inappropriate use of valid affixes (\"ally\" stemming to \"all\").  introduce a semantic-based algorithm for learning morphology which only proposes affixes when the stem and stem-plus-affix are sufficiently similar semantically.  implement our approach using Latent Semantic Analysis and show that our semantics-only approach provides morphology induction results that rival a current state-of-the-art system."}]