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Layers of Core Text Mining
At the lowest level, linguistic analysis and NLP techniques aim to identify key concept descriptors (who/what/where/when) embedded in textual documents. Different types of linguistic analysis techniques have been developed. Word and inverted indexing can be combined with stemming, morphological analysis, Boolean, proximity, range and fuzzy search. The unit of analysis is 'word'. Phrasal analysis, on the other hand, aims to extract meaningful noun phrase units or entities (e.g., people names, organisation names, location names). Both linguistic and statistical analysis techniques are plausible. In addition, semantic analysis based on techniques, such as, semantic grammar and case grammar can be used to represent semantics (meaning) in sentences. Semantic analysis is domain specific and lacks scalability. This often requires a significant knowledge base or a domain lexicon creation effort and hence it may not be suitable for general-purpose text mining across a wide spectrum of domains.
Changing Scenario and Driving Forces Over the past few decades, the economy of industrialised societies evolved from industrial economy to information economy and on to knowled
#quesgtion. growth of hrm
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what are the merits and demerits of time and output wages
Telephone Interview: The telephone interviews is used when the information to be collected is limited. The telephone interview is used i lieu of personal interviews. It is most
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Bulletin boards getting listing from employers there are many of whom pay a fee to have jobs listed-or sourced from newspapers, etc.
Presentation of operations and knowledge: this is the most important step in a training programme. The trainer should clearly tell show illustrate and question in order to put ove
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