Pyung Kim

On co-authorship for author disambiguation

Author name disambiguation deals with clustering the same-name authors into different individuals. To attack the problem, many studies have employed a variety of disambiguation features such as coauthors, titles of papers/publications, topics of articles, emails/affiliations, etc. Among these, co-authorship is the most easily accessible and influential, since inter-person acquaintances represented by co-authorship could discriminate the identities of authors more clearly than other features. This study attempts to explore the net effects of co-authorship on author clustering in bibliographic data. First, to handle the shortage of explicit coauthors listed in known citations, a web-assisted technique of acquiring implicit coauthors of the target author to be disambiguated is proposed. Then, a coauthor disambiguation hypothesis that the identity of an author can be determined by his/her coauthors is examined and confirmed through a variety of author disambiguation experiments.

Construction of a large-scale test set for author disambiguation

Author disambiguation resolves same-name author occurrences in the bibliographic data into namesakes. This enables author-centered searches and high-quality social network analysis. As an attempt to promote much research in author disambiguation, KISTI have constructed a new large-scale test set for this field. This article describes its semi-manual creation procedures, characteristics especially in terms of author ambiguities and name diversities. In addition, the baseline performance of author clustering against the test set is provided.

OntoFrame s3: semantic web-based academic research information portal service empowered by STAR-WIN

We have developed a prototype of a practical knowledge-driven semantic portal, OntoFrame S3, which provides various reasoning-based analysis services on academic research information. To realize this semantic portal, we developed and applied several Semantic Web and linguistic technologies. Through this demonstration, we will show how Semantic Web technologies can be utilized for information connection and fusion in the academic research information service sector and empowered by linguistic knowledge.

Decision-Making Support Service Based on Technology Opportunity Discovery Model

This paper discribes InSciTe Advanced, a decision-making support service, based on TOD(technology opportunity discovery) model. TOD model is a logical model for discovery of emerging technologies and prediction of phase and speed on a technology life cycle. InSciTe Advanced is based on semantic technologies such as ontology, semantic repository and inference as well as text mining. It aims to provide multi-facet services on emerging technologies, their elements and alternations in all domain. InSciTe Advanced has major services such as trends and predictions, technology levels, relationship paths, roadmaps and competitiors and collaborators.

Efficient Finding Relationship between Individuals in a Mass Ontology Database

Recently, as ontology is used in the semantic web, the amount of ontology instances is increasing explosively. Today’s world is complex, and so are the relationships within most knowledge domains. Especially a very complicated relationship cannot easily be overlooked. So, Experts to need decision making and information analysis expend a lot of time and effort on finding the relationships between individuals in many situations. To detect and extract relationships between individuals of interest with the help of a machine, the relationship finder system, namely RelFinder, is proposed. However, RelFinder cannot find all relationship because of its constraints for the system response time. Therefore, we propose the novel relationship finding system, named OntoRelFinder. OntoRelFinder utilizes schema paths and SPARQL endpoints to find the relationship between ontology individuals.

Features for Author Disambiguation

There exists a many-to-many mapping relationship between persons and their names. A person may have multiple names, and different persons may share the same name. These synonymous and homonymous names may severely deteriorate the recall and precision of the person search, respectively. This study addresses the characteristics of features for resolving homonymous author names appearing in citation data. As disambiguation features, previous works have employed citation-internal features such as co-authorship, titles of articles, titles of publications as well as citation-external features such as emails, affiliations, Web evidences. To the best of our knowledge, however, there has been no literature to deal with the influences of features on author disambiguation. This study analyzes the effect of individual features on author resolution using a large-scale test set for Korean.

Multi-faceted Navigation of Legal Documents

It is common that certain areas are dominated by one or two central laws, and furthermore legal documents are highly inter-linked and inter-dependent in legal domain. To help people in the domain to understand the complex relations between legal document fragments, a prototypical legal domain navigator is designed and implemented mainly using Semantic Web technologies. It makes the relations more visible and accessible to users with two different views: document and thesaurus views. We plan to expand the prototype to a real service after collecting sufficient opinions on this prototype from legal experts.

A Large-scale Test Set for Author Disambiguation

To overcome article-oriented search functions and provide author-oriented ones, a namesake problem for author names should be solved. Author disambiguation, proposed as its solution, assigns identifiers of real individuals to author name entities. Although recent state-of-the-art approaches to author disambiguation have reported above 90% performance, there are few academic information services which adopt author-resolving functions. This paper describes a large-scale test set for author disambiguation which was created by KISTI to foster author resolution researches. The result of these researches can be applied to academic information systems and make better service. The test set was constructed from DBLP data through web searches and manual inspection, Currently it consists of 881 author names, 41,673 author name entities, and 6,921 person identifiers.

Technology-based decision-making support system

This paper describes a decision-making support system focused on technologies, R&D agents, and R&D results. To deal with heterogeneous literatures and metadata, we introduce text mining and Semantic Web-based service platforms. InSciTe, a decision-making support system developed by us, provides a through process including analysis as well as ETL, verifies search and analysis results, connects its information with Semantic Web open sources in the level of RDF, and generates automatic summary reports. This system is significant in the sense that it has been implemented about a year earlier than similar projects such as CUBIST and FUSE.

Using semantic web technologies for technology intelligence services

The change in technological environment presents threats as well as opportunities to companies in the related fields. Existing Technology Intelligence procedures require complicated techniques and high-skilled labor results. Large expert-interviews and manual work is also needed, so single small companies can not undertake this alone. To spread and activate Technology Intelligence in research and industrial fields, we propose shallow, but automated, Technology Intelligence services based on Semantic Web technologies, which can reduce the amount of labor required from experts. We explain our Semantic Web technologies, such as ontology modeling, semantic repository, inference and verification and how they make our Technology Intelligence services possible.