Natural Language Processing has matured a lot recently. With the availability of great open source tools complementing the needs of the Semantic Web we believe this field should be on the radar of all software engineering professionals.

1. Natural Language Processing Quick Introduction Rohit Nayak Talentica Software

4. I have a dream for the Web [in which computers] become capable of analyzing all the data on the Web – the content, links, and transactions between people and computers. A ‘Semantic Web’, which should make this possible, has yet to emerge, but when it does, the day-to-day mechanisms of trade, bureaucracy and our daily lives will be handled by machines talking to machines. The ‘ intelligent agents ’ people have touted for ages will finally materialize. – Tim Berners -Lee , 1999

6. Text Categorization Is the document about plants? sports? health and fitness? corporate acquisitions? … stock market? Document

7. Sentiment Classification Is the overall sentiment in the document positive? negative? In general, sentiment classification appears to be harder than categorizing by topic. Document

8. Information Extraction Information Extraction System text collection Who: _____ What: _____ Where:_____ When: _____ How: _____ Who: _____ What: _____ Where:_____ When: _____ How: _____ Who: _____ What: _____ Where:_____ When: _____ How: _____

21. Rule: Company1 Priority: 25 ( ({Token.orthography == upperInitial})+ {Lookup.kind == companyDesignator} ):companyMatch --> :companyMatch.NamedEntity = {kind = "company", rule = "Company1"}