MUN Y. YI19-09-2011

KAIST Project

Creating Knowledge Out of Interlinked Data

Agenda

Introduction of KAISTKAIST LOD TeamDescription of Work

Tasks Deliverables

Current Status

Introduction of KAIST

KAIST (Korea Advanced Institute of Science and Technology) is the first and top science and technology research university in Korea.

Founded in 1971 to raise elites in science and technology

Located in the Daedeok Research Complex in the city of Daejeon, 150 kilometers south of Seoul.

For the 2009 academic year, over 8000 students enrolled; 3452 in the bachelor’s, 2197 in the master’s, and 2357 in the doctorate program. KAIST has 842 professors and 334 staff members as of January 2009

According to QS World University Rankings 2011, KAIST is ranked as the 90th in the World and 2nd in Korea.

KAIST LOD Team

Key-Sun Choi Director of Semantic Web Research Center Head of the Computer Science Department Expertise in ontology, NLP, and semantic Web

Mun Y. Yi Director of Knowledge Systems Lab Associate professor in the Knowledge Service Engineering Department Expertise in knowledge engineering, recommender systems, e-learning,

and MIS/HCI In-Young Ko

Director of WebEng Lab Associate professor in the Computer Science Department Expertise in software engineering and Web engineering including Web

services, Web-based information management, and semantic Web Ying Liu

Director of Intelligent System and Service Lab Assistant professor in the Knowledge Service Engineering Department Expertise in Tableseer, information retrieval, and text mining

Work Description: Tasks

Task 3.2: Provenance-Aware Linked Data Extraction from Unstructured and Semi-Structured Sources KAIST will add its experience in extracting Linked Data from Korean resources. KAIST has the most advanced technology in processing

Korean natural language resources and data. One example of such resource is CoreNet, which contains a taxonomic hierarchy, concept definitions and frame sets for Korean, Japanese and Chinese words. KAIST will build a Korean version of NLP2RDF by integrating various Korean natural language tools and providing the result of those toolkits in RDF format. KAIST will also facilitate the standardization of NLP2RDF through its involvement in the ISO group TC37/SC4 (Language Resources Management).

Task 4.1: Semi-Automatic Data Interlinking KAIST will contribute to this task by providing a platform for automatic linking with Korean, Chinese, Japanese RDF resources. CoreNet

contains a hierarchical concept structure for Korean, Chinese and Japanese words. Once the concepts of CoreNet are mapped to WordNet synsets, as WordNet is already integrated into LOD, KAIST can provide the Korean, Chinese and Japanese RDF data integration platform for Linked Data by providing a mapping mechanism of those data to CoreNet, thus solving multilingual issues for these Asian languages. KAIST has taken the initial step of the CoreNet-WordNet mapping; already showing some progress

Task 4.5a: Multilingual Linked Data Fusion KAIST will choose the DBpedia dataset as the pivot multilingual dataset, since it is extracted from various kinds of languages. KAIST will

work on the multilingual fusion of those multilingual DBpedia datasets, thus eliminating issues for other multilingual resources, since they simply need to fuse with their own language DBpedia resource. As a first step, KAIST is working on the bilingual fusion between the Korean DBpedia and the English DBpedia; having already obtained some results. At the end of the project these results will be expanded to the fusion of Chinese and Japanese DBpedia with Korean and English DBpedia. We envision to reach more than 90% precision and recall with this multi-lingual fusion approach.

Task 6.4: Development of application scenarios and testing of the LOD2 stack configurator The stack configurator will enable potential users to create their own personalized version of the LOD2 Stack, which contains only those

functions relevant for their usage scenarios. In this task, LOD2 partners will conduct an in-depth analysis of different application scenarios and identify LOD2 functional components that adequately respond to specific application requirements. These results of the study will be used to assist the development of the stack configurator and to prepare comprehensive LOD2 documentation both from the engineer’s and the user’s viewpoint.

Task 10.2d: Training and Dissemination in Korea (KAIST). KAIST will ensure the penetration of LOD2 results in a dynamic Asian country by organizing a number of events and outreach activities,

such as: Two research-oriented Data Web symposia aiming to bring together relevant researchers in Asia with the LOD2 consortium, Two industry workshops aiming at disseminating LOD2 results to Korean and Japanese companies and to facilitate cooperation and market entry of

industrial LOD2 partners, One Asian Data Web summer school aiming to outreach to PhD students and young researchers.

Work Description: Deliverables

Deliverable 3.2.4 Korean NLP2RDF (KAIST, M32) Initial release of the NLP2RDF framework for Korean text. This will include various

Korean NLP tools and data, including CoreNet. Compared to English, Korean NLP toolkits are less developed and opened; hence, most of the time will be devoted to the new development of Korean NLP tools which will contribute to LOD.

Deliverable 4.1.3 Korean Resource Linking Assist Release (M24) The first version of Korean resource linking assist to DBpedia will intelligently

recommend and order the possible mappings to the knowledge engineer. This will be implemented as the expansion of Deliverable 4.1.1.

Deliverable 4.1.4 Asian Resource Linking Assist Release (M30) This tool will help the knowledge engineer to link Korean, Chinese, Japanese

language resources to Linked Data by recommending and ordering appropriate mappings to her.

Deliverable 4.5.3 Korean Data Fusion Assistant (M30) The component will support Korean data fusion into English LOD by combining

Deliverable 4.5.1 with the fused dataset of English and Korean DBpedia. More precisely, the component will first fuse the new Korean dataset into Korean DBpedia by using D4.5.1, and the result will again be fused into the English DBpedia by applying the fusion result of Korean and English DBpedia.

Deliverable 4.5.4 Asian Data Fusion Assistant (M36) The component is an extension of Deliverable 4.5.3, and will support the data fusion

of Korean, Japanese and Chinese datasets.

Current Status

In preparation for a proposal to Korea MKE (Korea Ministry of Knowledge and Economy) Need to involve industry partners

Potential projects/applications CoreNet to LOD Korean NLP2RDF Multilingual DBPedia matching and expansion Link Korea Traditional Knowledge DB to LOD

Have similar work done in China and Japan Wiki History and Wiki Q&A Korean Wiki annotation