ontoblog: informal knowledge management by semantic blogging aman shakya 1, vilas wuwongse 2,...

23
OntoBlog: Informal Knowledge Management by Semantic Blogging Aman Shakya 1 , Vilas Wuwongse 2 , Hideaki Takeda 1 , Ikki Ohmukai 1 1 National Institute of Informatics, JAPAN 2 Asian Institute of Technology, Thailand

Post on 18-Dec-2015

217 views

Category:

Documents


0 download

TRANSCRIPT

OntoBlog: Informal Knowledge Management by Semantic Blogging

Aman Shakya 1, Vilas Wuwongse 2, Hideaki Takeda 1, Ikki Ohmukai 1

1 National Institute of Informatics, JAPAN

2 Asian Institute of Technology, Thailand

• Publicly accessible web-based publication of periodic articles usually in reverse chronological order

• Easy publishing platform• Dynamic media• Contributions from the community • Abundant collection of timely data

• Problems– Unstructured text– Filtering, organizing, navigating is difficult

Blogs

SKIMA 2008, Kathmandu, Nepal 2

Semantic Web“The Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation.”

The Semantic Web, Scientific American, May 2001,

Tim Berners-Lee, James Hendler and Ora Lassila

• The Semantic Web is about two things– Common formats for integration/combination of data drawn

from diverse sources– Language for recording how the data relates to real world

objectshttp://www.w3.org/2001/sw/

• Web of Linked Data• Current Challenge for the Semantic Web

– How to publish and use enough structured data easily?SKIMA 2008, Kathmandu, Nepal 3

Ontology in Semantic Web“An Ontology is an explicit specification of a

conceptualization”- Gruber (1993)

SKIMA 2008, Kathmandu, Nepal 4

Source: Tim Berners-Lee (XML2000)

Fig: The Semantic Web Stack

Conceptualization

“.. the objects, concepts, and other entities that are presumed to exist in some area of interest and the relationships that hold among them”

Semantic Blogging• Builds upon traditional blogging• Provides semantic structure to blog items• Enrich blog entries with metadata

• Combine desirable features of Blogging + Semantic Web

• Some Semantic Blogging systems1. Semantic Blogging Demonstrator (Cayzer, HP labs)

2. Semantic Blogging using Haystack (Karger & Quan, MIT)

3. Semblog (Ohmukai & Takeda, NII)

4. semiBlog (Möller et al., DERI) (now renamed “Shift”)

5. SocioBiblog (Shakya et al., NII)

6. Structured Blogging (http://structuredblogging.org/ )

SKIMA 2008, Kathmandu, Nepal 5

Limitations of Current Works

• Authoring metadata is cumbersome• Limited semantic capabilities

– Linking semantically related blog entries– Navigating through semantically related

blog entries– Searching and organizing relevant blog

entries

• Problems of traditional blogging still remain!

SKIMA 2008, Kathmandu, Nepal 6

Semantic Blogging forInformal Knowledge Management

• Semantic Blog– Capture knowledge of individuals informally– Not rigid as conventional database driven systems

• Annotate information snippets in blogs with semantically structured information– Link, Organize and Retrieve them effectively

• Utilize Knowledge Base technologies – Ontology and instances– Exploit the semantic links in Ontology

SKIMA 2008, Kathmandu, Nepal 7

Linking Blogs and Ontology

SKIMA 2008, Kathmandu, Nepal 8

Blog entries OntologySemantic Annotation

The OntoBlog Platform• Semantic Annotation

– Annotate blog entries with existing ontology instances

• Integrated Authoring– Authoring and annotation of blog entries

• Semi-automatic Annotation– Suggest related instances automatically

• Integrated Services– Semantic navigation, search and organization

• Feedback for Ontology Maintenance– Suggest new concepts and instances

Online demo - http://dutar.ex.nii.ac.jp/ontoblog/blog/default/

SKIMA 2008, Kathmandu, Nepal 9

Application Scenario

SKIMA 2008, Kathmandu, Nepal 10

Implementation

SKIMA 2008, Kathmandu, Nepal 11

Blog-Ontology Linking

• Simple language processing techniques– very fast and quite effective

• For each ontology instance, a “keywords” element contains a collection of related words

• Stemmed blog entries matched against stemmed “keywords”

• Related instances automatically suggested when adding/updating blog entries

• Discovered relations stored (if the user approves)

SKIMA 2008, Kathmandu, Nepal 12

SKIMA 2008, Kathmandu, Nepal 13

Authoring Blog Entry

Next…

Automatic Suggestions for semantic annotation

SKIMA 2008, Kathmandu, Nepal 14

Example Ontology

(Computer science department domain)

SKIMA 2008, Kathmandu, Nepal 15

• Populated and maintained using Protégé• OWL micro reasoner for Inference

Blog-Ontology Linking

SKIMA 2008, Kathmandu, Nepal 16

InstanceInstances in s in

OntologyOntology

Blog Blog EntrieEntrie

ss

Semantic Navigation

SKIMA 2008, Kathmandu, Nepal 17

Semantic Search

• Simple implementation to demonstrate applicability of semantic search

• Augment traditional search results– Return blog entries linked to semantically

related instances

• Useful when text search alone does not produce enough results

• Depth of semantic search can be controlled

SKIMA 2008, Kathmandu, Nepal 18

Semantic Aggregation

SKIMA 2008, Kathmandu, Nepal 19

Search Search resultsresultsRelated Related

EntriesEntriesclick

Feedback for Ontology Maintenance

• Users may suggest a new instance and/or concept• Useful for the administrator/knowledge engineer to

maintain the ontology – by adding missing concepts and instances or refining

them

SKIMA 2008, Kathmandu, Nepal 20

Conclusions

• Informal knowledge management can be done by semantic blogging

• OntoBlog – a Semantic Blogging prototype– Semi-automatic annotation of blog entries with existing

instances of Ontology

• Linking Blog and Ontology technologies

• Semantic structure of ontology enables semantic capabilities like Navigation and Organization in blogs

SKIMA 2008, Kathmandu, Nepal 21

Future and Ongoing Work

• Decentralized collaborative approach for Ontology

• Semantic capabilities across multiple blogs• Sophisticated language processing

– WordNet, IE (with supervised/unsupervised learning)

• Incorporate mature semantic search• Enhance inference capabilities• Ranked information retrieval

SKIMA 2008, Kathmandu, Nepal 22

Thank you !

• Questions / Suggestions

SKIMA 2008, Kathmandu, Nepal 23