• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.1162-1164
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• 2013

Top-k 질의 처리가 사용자가 원하는 데이터를 검색하는 방법인 반면에, Reverse Top-k 질의 처리는 데이터의 관점에서 특정 데이터를 가장 선호할 만한 사용자를 검색하는 방법으로 생산자의 입장에서 매우 중요한 연구이다. 본 논문에서는 Reverse Top-k 질의 처리 방법들을 소개하고 비교 및 문제점을 분석한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.1249-1252
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• 2011

최근 인터넷의 발달과 사용량의 증가로 데이터의 양이 급증하고 있다. 사용자들은 빠른 시간 내에 원하는 검색 결과를 얻기를 원한다. 또한 사용자 마다 모두 다른 선호도를 가지기 때문에 사용자 질의에 기반 하여 검색되어야 한다. 따라서 본 논문에서는 사용자 질의에 따라 빠른 시간 내에 효율적으로 List 기반의 접근법을 사용하여 top k 질의를 하는 기존의 연구를 소개 및 분석하고 문제점을 파악한다.

• The Journal of the Korea Contents Association
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• v.16 no.6
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• pp.205-214
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• 2016

As a large amount of graph-structured data is widely used in various applications such as social networks, semantic web, and bio-informatics, keyword-based search over graph data has been getting a lot of attention. In this paper, we propose an efficient method for keyword search over graph data to find a set of top-k answers that are relevant as well as non-redundant in structure. We define a non-redundant answer structure for a keyword query and a relevance measure for the answer. We suggest a new indexing scheme on the relevant paths between nodes and keyword terms in the graph, and also propose a query processing algorithm to find top-k non-redundant answers efficiently by exploiting the pre-calculated indexes. We present effectiveness and efficiency of the proposed approach compared to the previous method by conducting an experiment using a real dataset.

• The Journal of the Korea Contents Association
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• v.17 no.11
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• pp.209-220
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• 2017

As a semantic data is widely used in various applications such as Knowledge Bases and Semantic Web, needs for effective search over a large amount of RDF data have been increasing. Previous keyword search methods based on distinct root semantics only retrieve a set of answer trees having different root nodes. Thus, they often find answer trees with similar meanings or low query relevance together while those with the same root node cannot be retrieved together even if they have different meanings and high query relevance. We propose a new method to find diverse and relevant answers to the query by permitting duplication of root nodes among them. We present an efficient query processing algorithm using path indexes to find top-k answers given a maximum amount of root duplication a set of answer trees can have. We show by experiments using a real dataset that the proposed approach can produce effective answer trees which are less redundant in their content nodes and more relevant to the query than the previous method.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.5
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• pp.875-885
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• 2010

Recently, the role of Ubiquitous Sensor Network(USN) has been considered to be essential for supporting the near future Network Centric Warfare(NCW) and Tactical Information Communication Network(TICN). In this paper, we explore a set of data storage methods(external storage, local storage and data storage) and query processing methods in WSN. In particular, we focus on analyzing a novel data structure for supporting the local storage method, named the partial ordered tree(POT). The main idea behind POT is that sensor readings are usually correlated with the physical spatial domain. With the help of POT, only a small portion of sensor nodes participate in query processing tasks, and thus network lifetime is greatly increased. Through a series of simulation experiments, we demonstrate that the POT based local storage method clearly outperforms the existing data storage methods in terms of the energy-efficiency, which directly affects the network lifetime, for processing exact match queries, range queries and top-k queries.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.804-807
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• 2017

Top-k 질의란 주어진 조건을 만족하면서 높은 점수를 가진 상위 k개의 레코드를 요청하는 질의이다. 개체의 점수를 계산하는 랭킹함수가 단조함수가 아닐 경우 발생하는 기술적 어려움을 해결하기 위한 여러 연구가 있었다. 본 논문에서는 이들 중 각 차원이 선호 차원과 배척 차원으로 나뉘는 비단조 랭킹함수를 효율적으로 처리하는 기존의 top-k 질의 처리 기법들을 소개하고 비교한다.

• The KIPS Transactions:PartD
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• v.17D no.1
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• pp.17-24
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• 2010

Recently, there has been growing interest in skyline queries. Most of works for skyline queries assume that the data do not have null value. However, when we input data through the Web or with other different tools, there exist incomplete data with null values. As a result, several skyline processing techniques for incomplete data have been proposed. However, available skyline query techniques for incomplete data do not consider the environments that coexist complete data and incomplete data since these techniques deal with the incomplete data only. In this paper, we propose a novel skyline group processing technique which evaluates skyline queries for the environments that coexist complete data and incomplete data. To do this, we introduce the top-k(g) skyline group query which searches g skyline groups with respect to the user's dimensional preference. In our experimental study, we show efficiency of our proposed technique.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.723-724
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• 2009

무선 센서 네트워크에서 데이터 전송은 에너지를 소비하는 주 요인이다. 에너지를 줄이기 위한 주 기법 중 하나가 센서 데이터를 애그리게이션하여 전송할 데이터를 줄이는 것이다. 무선 센서 네트워크는 공개된 공간에서 진행되어 외부 공격에 취약점을 가지고 있으며, 기존 몇몇의 연구에서 애그리게이션 기법의 보안 기술을 제안하고 있다. 하지만, 기존의 기술들은 특정 연산자에만 제한되어 있고, 많은 유용성을 가진 top-k 질의에 대해서는 취약점을 가지고 있다. 본 논문에서는 무선 센서 네트워크에서 에너지 효율을 위한 애그리게이션 기법 적용시 top-k 질의를 효율적으로 처리할 보안 기법에 대해 제안한다.

• Journal of KIISE:Databases
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• v.33 no.5
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• pp.538-550
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• 2006

XML Keyword search enables us to get information easily without knowledge of structure of documents and returns specific and useful partial document results instead of whole documents. Element level query processing makes it possible, but computational complexity, as the number of documents grows, increases significantly overhead costs. In this paper, we present document-level ranking scheme over XML documents which predicts results of element-level processing to reduce processing cost. To do this, we propose the notion of 'keyword proximity' - the correlation of keywords in a document that affects the results of element-level query processing using path information of occurrence nodes and their resemblances - for document ranking process. In benefit of document-centric view, it is possible to reduce processing time using ranked document list or filtering of low scored documents. Our experimental evaluation shows that document-level processing technique using ranked document list is effective and improves performance by the early termination for top-k query.

• ETRI Journal
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• v.38 no.4
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• pp.714-723
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• 2016

Considerable attention has been given to processing graph data in recent years. An efficient method for computing the node proximity is one of the most challenging problems for many applications such as recommendation systems and social networks. Regarding large-scale, mutable datasets and user queries, top-k query processing has gained significant interest. This paper presents a novel method to find top-k answers in a node proximity search based on the well-known measure, Personalized PageRank (PPR). First, we introduce a distribution state transition graph (DSTG) to depict iterative steps for solving the PPR equation. Second, we propose a weight distribution model of a DSTG to capture the states of intermediate PPR scores and their distribution. Using a DSTG, we can selectively follow and compare multiple random paths with different lengths to find the most promising nodes. Moreover, we prove that the results of our method are equivalent to the PPR results. Comparative performance studies using two real datasets clearly show that our method is practical and accurate.