• IE interfaces
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• v.19 no.3
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• pp.225-235
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• 2006

In this paper, we propose an intelligent e-commerce meta-search engine which integrates distributed e-commerce sites and provides a unified search to the sites. The meta-search engine performs the following functions: (1) the user is able to create a category-based user query, (2) by using the WordNet, the query is semantically refined for increasing search accuracy, and (3) the meta-search engine recommends an e-commerce site which has the closest product information to the user’s search intention by matching the user query with the product catalogs in the e-commerce sites linked to the meta-search engine. An experiment shows that the performance of our model is better than that of general keyword-based search.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4771-4787
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• 2019

Aimed at the disclosure risk of mobile terminal user's location privacy in location-based services, a location-privacy protection scheme based on similar trajectory substitution is proposed. On the basis of the anonymized identities of users and candidates who request LBS, this scheme adopts trajectory similarity function to select the candidate whose trajectory is the most similar to user's at certain time intervals, then the selected candidate substitutes user to send LBS request, so as to protect user's privacy like identity, query and trajectory. Security analyses prove that this scheme is able to guarantee such security features as anonymity, non-forgeability, resistance to continuous query tracing attack and wiretapping attack. And the results of simulation experiment demonstrate that this scheme remarkably improve the optimal candidate' trajectory similarity and selection efficiency.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.4
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• pp.141-149
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• 1998

One of the difficulties in using the current Boolean-based information retrieval systems is that it is hard for a user, especially a novice, to formulate an effective Boolean query. One solution to this problem is to let the system formulate a query for a user from his relevance feedback documents in this research, an intelligent query reformulation mechanism based on ID3 is proposed and the sensitivity of its retrieval effectiveness, i.e., recall, precision, and E-measure, to various input settings is analyzed. The parameters in the input settings is the number of relevant documents. Experiments conducted on the test set of Medlars revealed that the effectiveness of the proposed system is in fact sensitive to the number of the initial relevant documents. The case with two or more initial relevant documents outperformed the case with one initial relevant document with statistical significances. It is our conclusion that formulation of an effective query in the proposed system requires at least two relevant documents in its initial input set.

• Journal of Multimedia Information System
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• v.4 no.3
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• pp.99-106
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• 2017

This study does a qualitative and quantitative analysis of how music by humming is being used by music educators in the classroom. Music by humming is part division of music information retrieval. In order to define what a music information retrieval system is first I need to define what it is. Berger and Lafferty (1999) define information retrieval as "someone doing a query to a retrieval system, a user begins with an information need. This need is an ideal document- perfect fit for the user, but almost certainly not present in the retrieval system's collection of documents. From this ideal document, the user selects a group of identifying terms. In the context of traditional IR, one could view this group of terms as akin to expanded query." Music Information Retrieval has its background in information systems, data mining, intelligent systems, library science, music history and music theory. Three rounds of surveys using question pro where completed. The study found that there were variances in knowledge, training and level of awareness of query by humming, music information retrieval systems. Those variance relationships where based on music specialty, level that they teach, and age of the respondents.

• Journal of the Korea Society of Computer and Information
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• v.22 no.12
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• pp.117-123
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• 2017

The personalized search algorithm is a search system that analyzes the user's IP, cookies, log data, and search history to recommend the desired information. As a result, users are isolated in the information frame recommended by the algorithm. This is called 'Filter bubble' phenomenon. Most of the personalized data can be deleted or changed by the user, but data stored in the service provider's server is difficult to access. This study suggests a way to neutralize personalization by keeping on sending random query words. This is to confuse the data accumulated in the server while performing search activities with words that are not related to the user. We have analyzed the rank change of the URL while conducting the search activity with 500 random query words once using the personalized account as the experimental group. To prove the effect, we set up a new account and set it as a control. We then searched the same set of queries with these two accounts, stored the URL data, and scored the rank variation. The URLs ranked on the upper page are weighted more than the lower-ranked URLs. At the beginning of the experiment, the difference between the scores of the two accounts was insignificant. As experiments continue, the number of random query words accumulated in the server increases and results show meaningful difference.

• Journal of KIISE:Software and Applications
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• v.27 no.2
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• pp.168-179
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• 2000

In reusable component retrieval systems with facet-based schemes, facet queries are generally used for representing the characteristics of components relevant to users. This paper proposes an expanded facet query equipped with an object-based thesaurus to precisely formulate user's intents. To evaluate the query, a component retrieval system is also designed and implemented. For exactly retrieving the components, user's query should include relevant facet values capable of fully specifying their characteristics. However, simply listing a series of facet values directly inputted by users, conventional queries fails to precisely represent user's intents. Our query, called expanded facet query, employs fuzzy boolean operators and object-based thesaurus; the former logically expresses the fuzzy connectives between facet queries and required components, whereas the latter helps users appropriately select the specific facet values into the query. A thesaurus query is provided to recommend the relevant facet values with their fuzzy degrees from the thesaurus as well. Furthermore, our retrieval system can automatically formulate queries with the recommended facet values, if necessary.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1986-1989
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• 2003

This paper proposes the information retrieval improvement for the Web using the structure and hyperlinks of HTML documents along with user profile. The method bases on the rationale that terms appearing in different structure of documents may have different significance in identifying the documents. The method partitions the occurrence of terms in a document collection into six classes according to the tags in which particular terms occurred (such as Title, H1-H6 and Anchor). We use genetic algorithm to determine class importance values and expand user query. We also use this value in similarity computation and update user profile. Then a genetic algorithm is used again to select some terms from user profile to expand the original query. Lastly, the search engine uses the expanded query for searching and the results of the search engine are scored by similarity values between each result and the user profile. Vector space model is used and the weighting schemes of traditional information retrieval were extended to include class importance values. The tested results show that precision is up to 81.5%.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.1
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• pp.21-32
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• 2010

User query formation highly acts on the effectiveness of information retrieval when we retrieve documents from the general domain as a web. This thesis proposes a intelligent information retrieval method based on a cross-lingual knowledge base to effectively perform a cross-lingual text retrieval from the web. The inferred knowledge from the cross-lingual knowledge base helps user's word association to make up user query easily and exactly for effective cross-lingual text information retrieval. This thesis develops user's query reformation algorithm and experiments it with Korean and English web. Experimental results show that the algorithm based on the proposed knowledge base is much more effective than without knowledge base in the cross-lingual text retrieval.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.4
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• pp.777-782
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• 2012

This paper proposes a technique for improving performance using word senses and user feedback in web information retrieval, compared with the retrieval based on ambiguous user query and index. Disambiguation using query word senses can eliminating the irrelevant pages from the search result. According to semantic categories of nouns which are used as index for retrieval, we build the word sense knowledge-base and categorize the web pages. It can improve the precision of retrieval system with user feedback deciding the query sense and information seeking behavior to pages.

• Journal of KIISE:Databases
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• v.35 no.2
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• pp.192-198
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• 2008

It is difficult to get relevant information on vast Web data. Search engines summarize and store Web information and show the ranked lists based on user queries affected by relative importance and user-adaptation. But these have limitation with showing user-intended information at the top priority. User intention is presented in general within query itself. In this paper, we propose the selective rankup methodology of user-intended search results based on weighting internal contiguity in query terms. With experimental results, we can find user-intended results with 75.8% probability using this simple method only, and efficiency of rerank proposed outperforms ordinary case by $13{\sim}20%$.