1 / 7

HYPERTEXT DATA BASES

HYPERTEXT DATA BASES. Session 7 16:10 - 16:35 Dr Soumen Chakabarti, IIT Bombay. Database evolution. Structured Operational Data. Additional data capture: free text from customer forms, phone conversation logs, etc. OLTP Operations. Semi- structured Database. SQL3: Text and

dawn-mack
Télécharger la présentation

HYPERTEXT DATA BASES

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. HYPERTEXT DATA BASES Session 7 16:10 - 16:35 Dr Soumen Chakabarti, IIT Bombay

  2. Database evolution StructuredOperational Data Additional data capture: free text from customer forms, phone conversation logs, etc. OLTP Operations Semi- structuredDatabase SQL3: Text and multimedia support Indexing, search and retrieval Data analysis and mining Collaboration and resource discovery

  3. Basic text indexing and retrieval • Inverted index mapping terms to (document, position) • Boolean search • socks and not “network* protocol*” • Phrase and proximity search • socks near(5) network* • Relevance ranking • Vector space model loan inflation bank

  4. Text mining • Problems • Very high dimensionality • Vocabulary mismatch • Available technologies • Relevance feedback • Semantic indexing • Semi-automatic thesaurus construction • Topic directory construction (clustering) • Topic directory maintenance (classification)

  5. From text to hypertext • Email, newsgroup, intranet web pages • Hyperlinks are much more than a browsing mechanism • Citations describe collective opinion • Hyperlinks implicitly form online communities • Hyperlinks enable collaboration and autonomous resource discovery

  6. Example: clustering and classification Organize resources used by employees into topic directory Classify news, email, office circulars, etc. into topic areas Discover resources on specific topics of interest on the Web Enable multiple users to collaborate without explicit effort

  7. Research problems • Represent and query semi-structured data • Mine distributed, hyperlinked data with both structured and unstructured fields • Locate Internet resources, understand their data schema, and enable data integration • Answer “why,” “how-to,” “where can I” questions in restricted domains • Unify text corpora with semi-structured thesaurus

More Related