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Explain the text mining applications
Based on significant research in the IR and the computational linguistics communities, it is generally agreed that phrasal-level analysis is more suited for coarse but scalable text mining applications. Word-level analysis is noisy and lacks precision. Sentence level is too structured and lacks practical applications. It is not coincidental that most of the subject headings and concept descriptors adopted by library classification schemes are noun phrases. Based on statistical and co-occurrence techniques, link analysis is performed to make automatic thesauri or conceptual associations of extracted methods. Existing human-created thesauri can also be integrated with system-generated thesauri.
It is important to remember that the review needs to comprise a critical evaluation of the subject area through the books and articles. You need to appraise the arguments and vie
Explain the Text mining in knowledge management Text mining is receiving considerable research and development attention. Content searching using a search engine based on a sea
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