Knowledge Discovery from WEB Search
Empirically Implementation Supervised Algorithms for Word Sense Disambiguation
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In recent years and because of popularity of computer and network, the search from the internet became important for everybody. Although search by keywords is the most efficient and popular method to find related information in the internet, it has two problems by using this relation. The first is that some search results do not match the user's requirement. The other reason is that there are too many similar articles in the search results, and because of these two problems, users spent a lot of time organizing the search results and finding what they really want. The knowledge discovery of se...
In recent years and because of popularity of computer and network, the search from the internet became important for everybody. Although search by keywords is the most efficient and popular method to find related information in the internet, it has two problems by using this relation. The first is that some search results do not match the user's requirement. The other reason is that there are too many similar articles in the search results, and because of these two problems, users spent a lot of time organizing the search results and finding what they really want. The knowledge discovery of sense with the help of context can be done with the help of Master-Slave algorithm. Word Sense Disambiguation is an open problem in Natural Language Processing. This problem is attempted with the help of various techniques like supervised, unsupervised learning algorithm and knowledge based algorithm. However, there is no concrete solution to this problem with good level of accuracy.
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