Showing papers by "Geun-Sik Jo published in 2010"

Constructing and mining a semantic-based academic social network

Abstract: A number of studies have focused on how to constructan academic social network. The relational ties among researchers are either co-authorship or shared keywords that are captured from scientific journals. The problem with such a network is that researchers are limited within their professional social network. In this paper, we propose a novel method for building a social network explicitly based on researchers’ knowledge interests. The researcher’s profile is automatically generated from metadata of scientific publications and homepage. By measuring the similarity between topics of interest, we are able to construct a researcher social network with relational linkages among authors that are produced by matching the their corresponding profiles. A direct loop graph-based social network is proposed. The graph naturally represents such a social network. Interestingly, our results showed that a social network based on profile matching is more representative than network based on publication co-authorship or shared keywords. Researcher mining in the academic social network has been explored via two problems Researcher Ranking and Expert Finding.

Contextual information search based on ontological user profile

Abstract: Internet users use the web to search for information they need. Every user has some particular interests and preferences when he/she searches information on the web. It is challenging to trace the exact interests of a user by a system to provide the information he/she wants. Personalization is a popular technique in information retrieval to present information based on an individual user's needs. The main challenges of effective personalization are to model the users and identify the users' context for accessing information. In this paper, we propose a framework to model the user details and context for personalized web search. We construct an ontological user profile describing the users preferences based on the users context. Finally, we use a semantic analysis of the log files approach for the initial construction of the ontological users profile and learn the profile over time. Web information can be accessed based on the ontological user profiles, re-ranking the searched results considering the users' context. Experiments show that our ontological approach to modeling users and context enables us to tailor the web search results for users based on users' interests and preferences.

Exploiting Script-Subtitles Alignment to Scene Boundary Dectection in Movie

Abstract: A movie, a typical multimedia data, includes several textual information such as subtitles and annotation texts as well as audio-visual information. In general, a story of a movie is progressed by dialogues of characters and the dialogues are produced based on a pre-written script that contains detailed descriptions of all the information related to the movie. The script consists of scene headings, character names, dialogues, actions, and so on. Rich information related to the movie can be extracted easily and accurately from each component of the script. However, since the script does not contain time information, additional processes are required to synchronize the script with the movie. The subtitle is usually made from the script’s dialogue and has time information to display text on screen when the characters speak. Therefore, synchronization between the script and the movie can be accomplished through an alignment process between the script’s dialogue and its’ subtitle. In this paper, we propose a unique method of scene boundary detection exploited script subtitles alignment. By synchronizing the script to movie, we identify scene boundaries with semantic level. In addition, we build a thesaurus to enhance alignment performance. Experimental results with real movies show that the proposed method can successfully, not only align scripts with those subtitles, but also detect scene boundaries.

The wordNet based semantic relationship between tags in folksonomies

Abstract: Collaborative tagging is a popular method in social resource sharing system. The reason why collaborative tagging system becomes popular is users can freely tags on the resources, like Flickr1 and Delicious2 . Any relationship between tags and resources are not made explicitly when tagging in folksonomy. Due to lack of semantic meaning, it is difficult for users to find related resources. Also, short of sufficient number of relevant tags increase the data sparsity which decreases the rate of information extraction against the user queries. Defining semantic relationship between tags, resources and users is an important research issue to retrieval of related information from folksonomies. In this paper, we propose a WordNet based method to find the semantic relationship between tags in folksonomy. Finally, the experiment results using Flickr data show our proposed method works well finding semantic relationship between tags in folksonomy.

Collaborative Digital Storytelling Platform with Collective Intelligence

Abstract: Due to the development of new digital technologies in recent years, consumers play different roles with compared to the past. Though they used to consume various existing contents, nowadays they have opportunities to use in user-friendly environment which can make them create and share their own contents. Under this circumstance, the digital storytelling has become a big issue in large area, and the web-based contents have been produced with diverse contests. In fact, the digital storytelling means a kind of storytelling method which is made by digital technologies and has been created under various circumstances. However, many researches concern that the digital storytelling is just applied for moving from analog to digital in terms of a tool, but in the reality it is far from the web 2.0 with collective intelligence. Therefore, in this paper, we propose a web-based collaborative digital storytelling platform that analysis user`s action processes and components applying collective intelligence.

Major Character Extraction using Character-Net

Abstract: In this paper, we propose a novel method of analyzing video and representing the relationship among characters based on their contexts in the video sequences, namely Character-Net. As a huge amount of video contents is generated even in a single day, the searching and summarizing technologies of the contents have also been issued. Thereby, a number of researches have been proposed related to extracting semantic in formation of video or scenes. Generally stories of video, such as TV serial or commercial movies, are made progress with chara cters. Accordingly, the relationship between the characters and their contexts should be identified to summarize video. To deal with these issues, we propose Character-Net supporting the extraction of major characters in video. We first identify characters appeared in a group of video shots and subsequently extract the speaker and listeners in the shots. Finally, the ch aracters are represented by a form of a network with graphs presenting the relationship among them. We present empirical experiments to demonstrate Character-Net and evaluate performance of extracting major characters.

An Effective Method for Ontology Integration by Propagating Inconsistency

Abstract: Ontology integration is an important task which needs to be performed when several information systems share or exchange knowledge We consider that most of previous methods of ontology integration merely involve blind or exhaustive matching among all concepts belonging to different ontologies Therefore, semantic mismatches, logical inconsistencies and conceptual conflicts between ontologies are unavoidable Additionally, the computational complexity increases rapidly in integrating large ontologies This research aims at investigating an effective methodology for ontology integration, in which, a propagating inconsistency algorithm has proposed to reduce complexity and mismatching in ontology integration A reconciled algorithm is suggested to generate a best representation from conflict concepts In evaluation, we compare our complexity of the algorithms and accuracy of the results with previous approaches’

An Emergency Alert Message Broadcasting System using Null-Packet on Digital TV Broadcasting

Abstract: In digital TV broadcasting, such as terrestrial, cable, satellite, and IPTV, the head-end of digital TV broadcasting has a more complicated transmission structure than that of analog TV broadcasting. Furthermore, digital TV broadcasting has a feature that supports multiplex models, such as Multiple Program Transport Stream (MPTS). Therefore, the purpose of our work was to design and examine a more efficient new system of emergency alert message transmission to support the digital TV broad-casting environments. Digital TV broadcasting is the IP generation or RF transmission of 8-VSB, QAM, and QPSK modulated through a multiplexer or re-multiplexer multiplexed stream as a MPEG-2 Transport Stream after content encoding. The new system proposed in this paper transmits an emergency alert message without scrambling after replacing the PID and payload of the null-packet with the message prototype in the TS stream from the multiplexer. If we need to transmit an emergency alert message under digital TV broadcasting services, then the receiver first checks the PID of each packet in the TS stream for the emergency alert message. Next, if a packet is determined to be an emergency alert message, then the set-top box displays the message on the TV screen using its function of On Screen Display, or the PC based software displays the message on the monitor screen using its function of overlay with user interface if the packet is found to be an emergency alert message. We have designed an emergency alert message protocol and a system model. By experiments and analysis of the system, we concluded that the system achieved efficiency and the ability to send and receive emergency alert messages using the system under different digital TV broadcasting service environments.

Collaborative Digital Storytelling based on Collective Intelligence through Contest

Abstract: Web development and digital technology enable users not only to consume contents but also to produce and share it through using various media. Thus, since personal needs for contents are increased, the interest in environment and technology for creating digital contents is growing. Because of existing digital contents technology such as writing tool or digital storyboard have focused on the individual creation, it is hard to induce participation and collaboration of other users and sharing and reusing contents. Therefore, we suggest a new form of collaborate digital storytelling using the concept of the collective intelligence through contest. Most of all, we develop writing tool and storyboard tool in order to facilitate participants to produce online contents. Also, distinguished from previous contest, this contest considers not only content output but also collaborative process for making it.