Against folksonomies: indexing blogs and podcasts for corporate knowledge management

Transcription

1 Against folksonomies: indexing blogs and podcasts for corporate knowledge management Isabella Peters Heinrich-Heine-University Düsseldorf Department of Information Science

2 Corporate Blogs and Podcasts Customer- Podcasts Knowledge- Blogs Campaigning- Blogs Product- Vodcasts Knowledgemanagement Service- Blogs Employee- Podcasts Crisis- Blogs CEO- Blogs

3 Indexing: How about folksonomies or tagging?

4 From chaos comes order. Aaron Weiss

5 Londra Power Law Users Tags zu f (x)= C/ x a 80/20-Rule London Travel UK England Tourism Guide Culture Information Entertainmen Holiday Londres Source: del.icio.us. Tags

6 Society Inverse-logistic Distribution Users Tags zu f (x)= e -C (x-1)b Associations Library Information Informationscience IA Technology Professional Research Usability Science Libraries Web Informationarchitecture IT Organizations Architecture Organzation Computers Conference Information_architecture Information_science Source: del.icio.us. Tags

7 Indexing with Folksonomy Source: Flickr.com (Yahoo!) Index terms (tags): A limited number of users can add or modify tags

8 Indexing with Folksonomy Studies show that: Manual tagging only groups articles into broad categories. Autotags extracted from top TFIDF- scored words produce better similarity scores and create more focused clusters. Source: Brooks, C.H.; Montanez, N. (2006). An Analysis of the Effectiviness of Tagging in Blogs.

9 Folksonomy vs. Ontology Whitehorse, maple leaf, dog lack of terminological checks no relations less precision huge search effort costumed dog synonym- and homonym check relations of hierarchy, abstraction, and association search is extendable less search effort Folksonomies are useful for observing user language.

10 Source: Krause, J. (1996): Schalenmodell. Indexing with Layer Model Fulltext Indexing Automatical Indexing with Ontologies Product -Blogs Employee -Blogs Intellectual Indexing with Ontologies CEO-Blog Decreasing Indexing Quality and Depth TDT

11 Topic Detection and Tracking automatic summary of content with similar topics popular application:

12 How does TDT work? Corporate Blogs Corporate Podcasts WWW Blogs, News & Podcasts Transcription Story Segmentation

13 How does TDT work? Story Segmentation New Topic? YES Link Detection with Similarity Algorithm NO Cluster Creation Cluster Detection

14 How does TDT work? Cluster Creation Cluster Detection Topic Tracking with Similarity Algorithm Title Creation Abstract Story Ranking

15 Advantages for Knowledge Management every blog / podcast is treated only once with TDT during its implementation in the Layer Model later appearing posts are automatically linked by TDT and indexed according to the model there are two documentary reference units: 1. blog / podcast as a whole 2. the topic

16 Example: Indexing of a CEO-Blog Re-Opening of the Factory in Duesseldorf Because of the factory s re-opening it is possible to increase our production by approximately 30%. More Blog as a whole: is indexed intellectually with Standard T h e s a u r u s Wirtschaft (German thesaurus for businnes matters) Topics: a) re-opening b) production the topic production is also mentioned in employee blogs topicisindexedintellectually with STW

17 Advantages for Researchers Are there any colleagues who work on the same topic as I do? Who knows this problem? Who is the expert in this field? you can track discussions across all blogs or podcasts topics with high relevance are indexed with high quality full text search is avoided search is more precise search is faster and gives better results

18 Summary: What s new? Folksonomy doesn t fulfil corporate knowledge management requirements but can observe user language. Layer Model for indexing according to information relevance and quality of corporate blogs and podcast. Automatic summary of blog posts and podcasts with Topic Detection & Tracking.

19 Many greetings from Düsseldorf. Contact:

20 References Allan, J. (2002). Topic Detection and Tracking. Event-based Information Organization. Kluwer Academic Publishers, Dordrecht, NL. Brooks, C.H.; Montanez, N. (2006). An Analysis of the Effectiviness of Tagging in Blogs. Available at Krause, J. (1996). Informationserschließung und -bereitstellung zwischen Deregulation, Kommerzialisierung und weltweiter Vernetzung Schalenmodell. Arbeitsbericht Informationszentrum Sozialwissenschaften, Nr. 6, Bonn. Shirky, C. (2004). Folksonomy. Available at Stock, W. (2006). Information Retrieval. Oldenbourg, München, Wien, Weiss, A. (2005). The Power of Collective Intelligence. In: networker 9 (3),