Introduction to Text Mining and Semantics, presented by Seth Grimes at Nstein seminars in London, June 2009, and New York, September 2009.

1. Introduction to Text Miningand Semantics Seth Grimes -- President, Alta Plana

2. New York Times October 9, 1958

3. From text to information “Text expresses a vast, rich range of information, but encodes this information in a form that is difficult to decipher automatically.” -- Marti A. Hearst, “Untangling Text Data Mining,” 1999

4. Document input and processing Information extraction Knowledge management Hans Peter Luhn, “A Business Intelligence System,” IBM Journal, October 1958

5. Statistical analysis of content “Statistical information derived from word frequency and distribution is used by the machine to compute a relative measure of significance.” Hans Peter Luhn, “The Automatic Creation of Literature Abstracts,” IBM Journal, April 1958

6. Statistical analysis limitations “This rather unsophisticated argument on ‘significance’ avoids such linguistic implications as grammar and syntax... No attention is paid to the logical and semantic relationships the author has established.” -- Hans Peter Luhn, 1958

7. Semantic links New York Times, September 8, 1957 Anaphora / coreference: “They”

8. Digital content universe “The broadcast, media, and entertainment industries garner about 4% of the world’s revenues but already generate, manage, or otherwise oversee 50% of the digital universe.” “The Diverse and Exploding Digital Universe,” (IDC, 2008) Approximately 70% of the digital universe is created by individuals.

10. Blogs, forum postings, and social media.

11. E-mail, Contact-center notes and transcripts; recorded conversation.

12. Surveys, feedback forms, warranty & insurance claims.

13. Office documents, regulatory filings, reports, scientific papers.

14. And every other sort of document imaginable.Is Search up to the job?

15. Search results How are the quality, value & authority of search results? Hotel’s opinion Who profits from search? Guest’s opinion - about Priceline

16. From Web 1.0 to Web 2.0 How can we do better? “We have many of the tools in place -- from Web 2.0 technologies…” “The Diverse and Exploding Digital Universe,” (IDC, 2008)

17. Web 2.0 “Web 2.0 is the business revolution in the computer industry caused by the move to the Internet as a platform.” -- Tim O’Reilly, 2004 “[A] move from personal websites to blogs and blog site aggregation, from publishing to participation,… an ongoing and interactive process... to links based on tagging.” -- Terry Flew, “New Media: An Introduction,” 2008 Web 2.0 is dynamic, personalized, interactive, collaborative.

18. From information growth to economicgrowth “We have many of the tools in place -- from Web 2.0 technologies… to unstructured data search software and the Semantic Web -- to tame the digital universe. Done right, we can turn information growth into economic growth.” -- “The Diverse and Exploding Digital Universe,” (IDC, 2008)

19. Text mining: from information to intelligence Text mining enables smarter search that better responds to user goals, e.g., answers –

21. Linked Data.

22. Context sensitive.

24. Steps in the right direction…

25. … and missteps “Kind” = type, variety, not a sentiment. Complete misclassification External reference Unfiltered duplicates

27. Text augmentation: metadata generation, content tagging.

28. Information extraction to databases.

30. RDF, SPARQL, OWL

32. Primary applications What are your primary applications where text comes into play?

33. Analyzedtextual information What textual information are you analyzing or do you plan to analyze? Current users responded:

34. Extracted information Do you need (or expect to need) to extract or analyze:

35. Overall satisfaction Please rate your overall experience – your satisfaction – with text mining.

36. Movingahead Apply text mining to discover value in content. Develop / improve metadata and taxonomies. Adopt semantic technologies -- for content publishing and for user interactions -- to boost flexibility, findability, and profitability. And understand your audience: “By focusing on the fundamental aspects of the consumers’ online behavior -- not just current best practices -- companies will be better prepared when Web 2.0+ morphs into Web 3.0 and beyond.” -- Donna L. Hoffman, UC Riverside, in the McKinsey Quarterly