• Proceedings of the KAIS Fall Conference
• /
• 2006.11a
• /
• pp.290-293
• /
• 2006

The goal of research is to propose a framework for drawing data search system which is based on the web. The existing search systems were reviewed in the form of case studies and thereby the limitation were addressed: the unsystematic translation between the presentational building model and the discursive design criteria. besides the limited area in sharing and space. Therefore, a web-based drawing search with common structure which building representational model and building behavior model is proposed. The system contains a number of phases: firstly, a user is required to build a building model with the proposed building representational model and then this model is automatically transformed into an aspect model; secondly, a user is also required to present his query in form of the propose building behavior model by web page; finally, these two models - building representational model and building behavior model - are compared by database data so as to retrieve the proper result.

• The KIPS Transactions:PartB
• /
• v.12B no.2 s.98
• /
• pp.215-222
• /
• 2005

In this paper, a MetaSearch algorithm for navigational queries is presented. Previous MetaSearch algorithms focused on informational queries. They Eave a high score to an overlapped document. However, the overemphasis of overlapped documents may degrade the performance of a MetaSearch algerian for a navigational query. However, if a lot of result documents are from a certain domain or a directory, then we can assume the importance of the domain or directory. Various experiments are conducted to show the effectiveness of overlap of a domain and directory names. System results from TREC and commercial search engines are used for experiments. From the results of experiments, the overlap of documents showed the better performance for informational queries. However, the overlap of domain names and directory names showed the $10\%$ higher performance for navigational queries.

• Journal of the Korean Society for Library and Information Science
• /
• v.43 no.3
• /
• pp.163-180
• /
• 2009

In this paper, we describe a developmental system for establishing personal information tendency based on user queries. For each query, the system classified it based on the category information using a kNN classifier. As category information, we used DDC field which is already assigned to each record in the database. The system accumulates category information for all user queries and the user's personalized feature for the target database. We then developed a personalized retrieval system reflecting the personalized feature to produce search result. Our system re-ranks the result documents by adding more weights to the documents for which categories match with the user's personalized feature. By using user's tendency information, the ambiguity problem of the word could be solved. In this paper, we conducted experiments for personalized search and word sense disambiguation (WSD) on a collection of Korean journal articles of science and technology arena. Our experimental result and user's evaluation show that the performance of the personalized search system and WSD is proved to be useful for actual field services.

• Journal of the Korea Society of Computer and Information
• /
• v.14 no.2
• /
• pp.169-180
• /
• 2009

The conventional paper retrieval is the keyword-based search and as a huge amount of data be published, this search becomes more difficult in retrieving information that user want to find. In order to search for information to the user's intent, we need to introduce semantic Web that represents semantics of Web document resources on the Internet environment as ontology and enables the computer to understand this ontology. Therefore, we describe a paper retrieval system through OWL(Ontology Web Language) ontology-based reason in this paper. We build the paper ontology based on OWL which is new popular ontology language for semantic Web and represent the correlation among diverse paper properties as the DL(description logic) query, and then this system infers the correct results from the paper ontology by using the DL query and makes it possible to retrieve information intelligently. Finally, we compared our experimental result with the conventional retrieval.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.4
• /
• pp.1693-1713
• /
• 2018

An important technique used by database administrators (DBAs) is to improve performance in decision-support workloads associated with a Star schema is multi-level partitioning. Queries will then benefit from performance improvements via partition elimination, due to constraints on queries expressed on the dimension tables. As the task of multi-level partitioning can be overwhelming for a DBA we are proposing a wizard that facilitates the task by calculating a partitioning scheme for a particular workload. The system resides completely on a client and interacts with the costing estimation subsystem of the query optimizer via an API over the network, thereby eliminating any need to make changes to the optimizer. In addition, since only cost estimates are needed the wizard overhead is very low. By using a greedy algorithm for search space enumeration over the query predicates in the workload the wizard is efficient with worst-case polynomial complexity. The technology proposed can be applied to any clustering or partitioning scheme in any database management system that provides an interface to the query optimizer. Applied to the Teradata database the technology provides recommendations that outperform a human expert's solution as measured by the total execution time of the workload. We also demonstrate the scalability of our approach when the fact table (and workload) size increases.

• Journal of the Korean Society for information Management
• /
• v.22 no.2 s.56
• /
• pp.41-56
• /
• 2005

For the purpose of extending the Web that is able to understand and process information by machine, Semantic Web shared knowledge in the ontology form. For exquisite query processing, this paper proposes a method to use semantic relations in the ontology as relevance feedback information to query expansion. We made experiment on pharmacy domain. And in order to verify the effectiveness of the semantic relation in the ontology, we compared a keyword based document retrieval system that gives weights by using the frequency information compared with an ontology based document retrieval system that uses relevant information existed in the ontology to a relevant feedback. From the evaluation of the retrieval performance. we knew that search engine used the concepts and relations in ontology for improving precision effectively. Also it used them for the basis of the inference for improvement the retrieval performance.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.8 no.2
• /
• pp.280-285
• /
• 2007

This paper proposes a technique 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 word senses is very important processing for improving performance by eliminating the irrelevant pages from the 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 performance of retrieval system with user feedback deciding the query sense and information seeking behavior to web pages.

• Journal of KIISE:Databases
• /
• v.31 no.1
• /
• pp.72-81
• /
• 2004

Theses days, a number of data over the Internet are represented using XML because of a virtue of XML. In proportion to the increase of XML data, query processing techniques are required that support quickly and efficiently the diverse queries to search the useful information on XML documents. But, up to now, the researches handling queries for XML data are methodologies focusing on how to process regular path expressions. Therefore, we have developed a new genealogy-based indexing technique to solve various queries such as not only regular path expression but also simple path expression, path expression referencing other elements, and so on. Also, we have applied this technique on object-relational model and evaluated the performance for many documents and various query types. The result shows improved performance in comparison with the other storage techniques.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.47 no.1
• /
• pp.146-151
• /
• 2010

For an application of ontology, query processing is mandatory field for efficient information search in the ontology. Other query processing systems tend to analyze only facts and to simply provide structural information for users. In fact, the systems do not have big difference with database systems or text based information processing systems. Therefore, in this research, the method which can provide the inferred information based on axioms is suggested in order to maximize reusability of ontology.

• Journal of KIISE:Software and Applications
• /
• v.32 no.11
• /
• pp.1013-1020
• /
• 2005

This paper presents an effective and robust leaf image retrieval system based on shape feature. Specifically, we propose an improved MPP algorithm for more effective representation of leaf images and show a new dynamic matching algorithm that basically revises the Nearest Neighbor search to reduce the matching time. In particular, both leaf shape and leaf arrangement can be sketched in the query for better accuracy and efficiency. In the experiment, we compare our proposed method with other methods including Centroid Contour Distance(CCD), Fourier Descriptor, Curvature Scale Space Descriptor(CSSD), Moment Invariants, and MPP. Experimental results on one thousand leaf images show that our approach achieves a better performance than other methods.