Juntae Kim

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Recommendation systems analyze user preferences and recommend items to a user by predicting the user's preference for those items. Among various kinds of recommendation methods, collaborative filtering (CF) has been widely used and successfully applied to practical applications. However, collaborative filtering has two inherent problems: data sparseness and(More)
This paper presents the SERF (System for Electronic Recommendation Filtering) which is a collaborative filtering system that recommends context-sensitive, high-quality information sources for document search. Collaborative filtering systems remove the limitation of traditional content-based search by using individual's ratings to evaluate and recommend(More)
Social networks are social structures that depict relational structure of different entities. The most important entities are usually located in strategic locations within the network. Users from such positions play important roles in spreading the information. The purpose of this research is to make a connection between, information related to structural(More)
DBSCAN is one of powerful density-based clustering algorithms for detecting outliers, but there are some difficulties in finding its parameters (epsilon and minpts). Currently, there is also no way to use DBSCAN with different parameters for different cluster when it is applied to anomaly detection when network traffic includes multiple traffic types with(More)
In this paper, we propose a two-step method to reduce wind noise in dual microphone environments. Wind noise in outdoors recording often leads to critical degradation to the speech signal. Therefore, it is necessary to apply algorithms for reduction of wind noise. The proposed algorithm exploits the coherence of input signals and use a Wiener filter to(More)
Overlapping speech is known to be the major source of error in various speech processing algorithm. Many previous studies on overlapping speech detection focus on exploring the various feature set for representing speech and overlapping speech characteristics while using the HMM framework. In this study, however, we hypothesize that the capacity of single(More)
Voice activity detection (VAD) determines whether the incoming signal segments are speech or noiseand is an important technique in almost all of speech-related applications. In order to improve VAD performance in various noise environments, characterizing the speech feature has been the most crucial issue up to date. Among several proposed speech features,(More)