• The Journal of the Acoustical Society of Korea
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• v.16 no.5
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• pp.92-95
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• 1997

Thlephone pushbuttons simply consist of 0~9 digits, #, and ${\ast}$). So it is difficulty for user to input the various query command for information retrieval of audio response sevice. We suggest the new retrieval algorithm for audio response service using Korean initial sounds sequences. User those who do not know the retrieval code can retrieve the audio response service by pushing the telephone digit buttons which correspond to initial sounds of its name.

• The Journal of the Korea Contents Association
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• v.8 no.12
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• pp.45-52
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• 2008

The Object Directory Service(ODS) of the mobile RFID is the core technology of the object information service for the object information retrieval among objects with RFID tags. The ODS service returns an URL information of a specific object application service after recognizing the mRFID tag in real time. The general ODS service is suitable for the global mRFID environment, but it is not good in the local networks and private networks that information security is needed. This paper proposes a new ODS service algorithm for the improvement of the general ODS service algorithm.

• Journal of the Korea Society for Simulation
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• v.14 no.2
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• pp.1-13
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• 2005

In distributed replicating server model, providing replicated services is able to improve the performance of providing a service and efficiency for several clients. And, the composition of the server selection algorithm is efficiently able to decrease the retrieval time for replicated data. In this paper, we define the system model that selects and connects the replicated server that provides optimal service using server-side downstream measurement and proposes an applicable algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2211-2232
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• 2018

The unstructured and semi-structured big data in social network poses new challenges in query retrieval. This requirement needs to be met by introducing quality retrieval time measures like indexing. Due to the huge volume of data storage, there originate the need for efficient index algorithms to promote query processing. However, conventional algorithms fail to index the huge amount of frequently obtained information in real time and fall short of providing scalable indexing service. In this paper, a new LIndex algorithm, which is a heuristic on Lucene is built on Neo4jHA architecture that holds the social network Big data. LIndex is a flexible and simplified adaptive indexing scheme that ascendancy decomposed shortest paths around term neighbors as basic indexing unit. This newfangled index proves to be effectual in query space pruning of graph database Neo4j, scalable in index construction and deployment. A graph query is processed and optimized beyond the traditional Lucene in a time-based manner to a more efficient path method in LIndex. This advanced algorithm significantly reduces query fetch without compromising the quality of results in time. The experiments are conducted to confirm the efficiency of the proposed query retrieval in Neo4j graph NoSQL database.

• Journal of Information Processing Systems
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• v.2 no.2
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• pp.130-134
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• 2006

In the distributed replicating server model, the provision of replicated services will improve the performance of the providing service and efficiency for clients. Efficiently composing the server selection algorithm decreases the retrieval time for replicated data. In this paper, we define the system model that selects and connects the replicated server that provides an optimal service using the server-side downstream measurement and propose a server selection algorithm.

• Journal of Korea Multimedia Society
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• v.13 no.8
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• pp.1245-1255
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• 2010

In current Web 2.0 environment, one of the most core technology is social bookmarking which users put tags and bookmarks to their interesting Web pages. The main purpose of social bookmarking is an effective information service by use of retrieval, grouping and share based on user's bookmark information and tagging result of their interesting Web pages. But, current social bookmarking system uses the number of bookmarks and tag information separately in information retrieval, where the number of bookmarks stand for user's degree of interest on Web contents, information retrieval, and classification serve the purpose of tag information. Because of above reason, social bookmarking system does not utilize effectively the bookmark information and tagging result. This paper proposes a Web contents ranking algorithm combining bookmarks and tag information, based on preceding research on associative tag extraction by tag clustering. Moreover, we conduct a performance evaluation comparing with existing retrieval methodology for efficiency analysis of our proposed algorithm. As the result, social bookmarking system utilizing bookmark with tag, key point of our research, deduces a effective retrieval results compare with existing systems.

• Journal of KIISE:Software and Applications
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• v.37 no.3
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• pp.214-221
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• 2010

The search-results clustering problem is defined as the automatic and on-line grouping of similar documents in search results returned from a search engine. In this paper, we propose a new search-results clustering algorithm specialized for a paper search service. Our system consists of two algorithmic phases: Category Hierarchy Generation System (CHGS) and Paper Clustering System (PCS). In CHGS, we first build up the category hierarchy, called the Field Thesaurus, for each research field using an existing research category hierarchy (KOSEF's research category hierarchy) and the keyword expansion of the field thesaurus by a word clustering method using the K-means algorithm. Then, in PCS, the proposed algorithm determines the category of each paper using top-down and bottom-up methods. The proposed system can be used in the application areas for retrieval services in a specialized field such as a paper search service.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.40-44
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• 1995

In this paper, we propose a retrieval system using knowledges of database expressed linguistically, where the relation between data are constructed by FCM. Several algorithms have been proposed to solve the major problem in the conventional retrieval system that the system doesn't reply in case of no data equal to user's query, and to express knowledge of database linguistically. This paper proposes the improved method of adding new cluster and the method of retrieving database from user's query. The validity of this retrieval system is shown by applying its algorithm to an example : the mail order service in post office.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.3
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• pp.1-10
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• 2018

Social network services allow you to share your thoughts and preferences more easily. They share your views with a large number of people who are friends with you without restriction of time or place. In the IoT environment, the amount of data is massively increasing as social network services spread rapidly. This change in the environment is driving the need for research into new retrieval methods that are different from conventional retrieval methods. In this paper, we propose a progressive retrieval method using the intimacy of social network users in the IoT. The first thing is to extract the user with the highest intimacy by using the property that the number of the owner of the information stored in the IoT environment is small. By accessing information in objects owned by these extracted users, the amount of information retrieved is reduced. It also improves retrieval efficiency by gradually retrieving information according to the user's level of interest. We present a new retrieval method and algorithm. The scenario also illustrates the effectiveness of the proposed method.

• International Journal of Contents
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• v.11 no.4
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• pp.1-6
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• 2015

In practice, the most important performance parameters for music information retrieval (MIR) service are robustness of fingerprint in real noise environments and recognition accuracy when the obtained query clips are matched with the an entry in the database. To satisfy these conditions, we proposed a conjoined fingerprint algorithm for use in massive MIR service. The conjoined fingerprint scheme uses interhash and intrahash algorithms to produce a robust fingerprint scheme in real noise environments. Because the interhash and intrahash algorithms are masked in the predominant pitch estimation, a compact fingerprint can be produced through their relationship. Experimental performance comparison results showed that our algorithms were superior to existing algorithms, i.e., the sub-mask and Philips algorithms, in real noise environments.