• Journal of Information Processing Systems
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• v.15 no.4
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• pp.737-747
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• 2019

Shape description is an important and fundamental issue in content-based image retrieval (CBIR), and a number of shape description methods have been reported in the literature. For shape description, both global information and local contour variations play important roles. In this paper a new included-angular ternary pattern (IATP) based shape descriptor is proposed for shape image retrieval. For each point on the shape contour, IATP is derived from its neighbor points, and IATP has good properties for shape description. IATP is intrinsically invariant to rotation, translation and scaling. To enhance the description capability, multiscale IATP histogram is presented to describe both local and global information of shape. Then multiscale IATP histogram is combined with included-angular histogram for efficient shape retrieval. In the matching stage, cosine distance is used to measure shape features' similarity. Image retrieval experiments are conducted on the standard MPEG-7 shape database and Swedish leaf database. And the shape image retrieval performance of the proposed method is compared with other shape descriptors using the standard evaluation method. The experimental results of shape retrieval indicate that the proposed method reaches higher precision at the same recall value compared with other description method.

• Journal of the Korean Society for information Management
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• v.2 no.2
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• pp.38-70
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• 1985

The purpose of this paper is to provide a review of the literature on the role of end-user intermediary systems in information retrieval. The paper starts with an introduction pointing out the problems involved in conventional retrieval system. The next section covers the major developments in the field of intermediary systems including natural language processing, automatic query formulation, relevance feedback, and automatic query refinement. The paper concludes with a general overview of the current state of the art and its future implications in information retrieval.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.5197-5218
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• 2019

Large-scale retrieval algorithm is problem for visual analyses applications, along its research track. In this paper, we propose a high-efficiency region division-based image retrieve approaches, which fuse low-level local color histogram feature and texture feature. A novel image region division is proposed to roughly mimic the location distribution of image color and deal with the color histogram failing to describe spatial information. Furthermore, for optimizing our region division retrieval method, an image descriptor combining local color histogram and Gabor texture features with reduced feature dimensions are developed. Moreover, we propose an extended Canberra distance method for images similarity measure to increase the fault-tolerant ability of the whole large-scale image retrieval. Extensive experimental results on several benchmark image retrieval databases validate the superiority of the proposed approaches over many recently proposed color-histogram-based and texture-feature-based algorithms.

• Journal of information and communication convergence engineering
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• v.9 no.3
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• pp.282-286
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• 2011

Recently, a name retrieval function is widely used on navigation systems. In this paper, we propose the new dynamic hashing algorithm for a name retrieval function on it. The proposed dynamic hashing algorithm by constructing an index using the variance information of character is the better than existing methods in terms of storage capacity and retrieval speed. The algorithm proposed in this paper can be useful on systems that have limited resources as well as navigation systems.

• Journal of the Korean Society for Library and Information Science
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• v.16
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• pp.177-205
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• 1989

Retrieval effectiveness is the principal criteria for measuring the performance of an information retrieval system. This paper deals with the characteristics of 'relevance' of information and various measuring techniques of retrieval effectivess. The outlines of this study are as follows: 1) Relevance decision for evaluation should be devided into the user-oriented and the system-oriented decisions. 2) The recall-precision measure seems to be user-oriented, and the recall-fallout measure to be system-oriented. 3) Many of composite measures can not be justified III any rational manner unfortunately. 4) The Swets model has demonstrated that it yields, in general, a straight line instead of a curve of varying curvature and emphasized the fundamentally probabilistic nature of information retrieval. 5) The Cooper model seems to be a good substitute for precision and a useful measure for systems which ranked documents. 6) The Rocchio model were proposed for the evaluation of retreval systems which ranked documents, and were designed to be independent of cut-off. 7) The Cawkell model suggested that the Shannon's equation for entropy can be applied to measuring of retrieval effectiveness.

• International Journal of Contents
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• v.1 no.2
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• pp.39-43
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• 2005

In this paper, we describe a generation mechanism of semantic-based queries for high accuracy information retrieval and question answering. It is difficult to offer the correct retrieval result because general information retrieval systems do not analyze the semantic of user's natural language question. We analyze user's question semantically and extract semantic features, and we .generate semantic-based queries using them. These queries are generated using the se-mantic-based question analysis grammar and the query generation rule. They are represented as semantic features and grammatical morphemes that consider semantic and syntactic structure of user's questions. We evaluated our mechanism using 100 questions whose answer type is a person in the TREC-9 corpus and Web. There was a 0.28 improvement in the precision at 10 documents when semantic-based queries were used for information retrieval.

• Journal of Computing Science and Engineering
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• v.6 no.2
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• pp.168-177
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• 2012

The search for relevant and actionable information is a key to achieving clinical and research goals in biomedicine. Biomedical information exists in different forms: as text and illustrations in journal articles and other documents, in images stored in databases, and as patients' cases in electronic health records. This paper presents ways to move beyond conventional text-based searching of these resources, by combining text and visual features in search queries and document representation. A combination of techniques and tools from the fields of natural language processing, information retrieval, and content-based image retrieval allows the development of building blocks for advanced information services. Such services enable searching by textual as well as visual queries, and retrieving documents enriched by relevant images, charts, and other illustrations from the journal literature, patient records and image databases.

• International Journal of Computer Science & Network Security
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• v.24 no.7
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• pp.31-44
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• 2024

The inverted index is combination of the keywords and posting lists associated for indexing of document. In modern age excessive use of technology has increased data volume at a very high rate. Big data is great concern of researchers. An efficient Document indexing in big data has become a major challenge for researchers. All organizations and web engines have limited number of resources such as space and storage which is very crucial in term of data management of information retrieval system. Information retrieval system need to very efficient. Inverted indexing technique is introduced in this research to minimize the delay in retrieval of data in information retrieval system. Inverted index is illustrated and then its issues are discussed and resolve by implementing the scalable inverted index. Then existing algorithm of inverted compared with the naïve inverted index. The Interval list of inverted indexes stores on primary storage except of auxiliary memory. In this research an efficient architecture of information retrieval system is proposed particularly for unstructured data which don't have a predefined structure format and data volume.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.6
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• pp.1129-1133
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• 2006

In this thesis, we propose a semantics-based video retrieval system which supports semantics-retrieval for various users of massive video data. Proposed system automatically processes the extraction of contents information which video data has and retrieval process using agent which integrate annotation-based retrieval and feature-based retrieval. From experiment, the designed and implemented system shows increase of recall rate and precision rate for video data scene retrieval in performance assessment.

• Journal of the Korean Society for information Management
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• v.28 no.2
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• pp.135-158
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• 2011

The ability of the searcher to express their information problem to an information retrieval system is fundamental to the retrieval process. Query by visual example is the principal query paradigm for expressing queries in a content-based image retrieval environment yet there is little empirical evidence to support its efficacy in facilitating query formulation. The aim of this research was to investigate the usability of the query by colour method in supporting a range of information problems in order to contribute to the gap in knowledge regarding the relationship between searchers' information problems and the query methods required to support efficient and effective visual query formulation. The results strongly suggest that the query method does not support visual query formulation and that there is a significant mismatch between the searchers information problems and the expressive power of the retrieval paradigm.