• Korean Journal of Child Studies
• /
• v.23 no.5
• /
• pp.1-17
• /
• 2002

The influence on children's analogical problem solving of structural highlighting during encoding and retrieval of sources was studied with 379 9-year-old participants. Performance on the first 2 of 4 tests determined the analogical level of each child. For the remaining 2 tests, the child was assigned to 1 of 12 different structural highlighting conditions, including 4 encoding conditions (reading, line, self-line, and self-explain) and 3 retrieval conditions (reminding, cued, and thematic comparison). Results showed that retrieval conditions, not encoding conditions, improved the analogical ability of the child. Children initially low in analogical ability improved in cued retrieval conditions; children initially high in analogical ability improved both in thematically compared and in cued retrieval conditions. Practical implications of the results were discussed.

• Journal of Information Processing Systems
• /
• v.11 no.3
• /
• pp.450-464
• /
• 2015

In linguistics, stemming is the operation of reducing words to their more general form, which is called the 'stem'. Stemming is an important step in information retrieval systems, natural language processing, and text mining. Information retrieval systems are evaluated by metrics like precision and recall and the fundamental superiority of an information retrieval system over another one is measured by them. Stemmers decrease the indexed file, increase the speed of information retrieval systems, and improve the performance of these systems by boosting precision and recall. There are few Persian stemmers and most of them work based on morphological rules. In this paper we carefully study Persian stemmers, which are classified into three main classes: structural stemmers, lookup table stemmers, and statistical stemmers. We describe the algorithms of each class carefully and present the weaknesses and strengths of each Persian stemmer. We also propose some metrics to compare and evaluate each stemmer by them.

• Journal of KIISE:Databases
• /
• v.30 no.3
• /
• pp.237-251
• /
• 2003

In this paper, we propose a video retrieval system to search logical structure and semantic contents of video data efficiently. The proposed system employs a layered modelling method that orBanifes video data in raw data layer, content layer and key frame layer. The layered modelling of the proposed system represents logical structures and semantic contents of video data in content layer. Also, the proposed system supports various types of searches such as text search, visual feature based similarity search, spatio-temporal relationship based similarity search and semantic contents search.

• Journal of Korea Multimedia Society
• /
• v.7 no.5
• /
• pp.601-616
• /
• 2004

Information retrieval systems for structured documents provide multiple levels of retrieval capability by supporting structure-based queries. In order to process structure-based queries for structured documents, information for structural nesting relationship between elements and for element sequence must be maintained. This paper presents four index structures that can process various query types about structures such as structural relationships between elements or element occurrence order. The proposed algorithms are based on the concept of Global Document Instance Tree.

• Journal of the Korean Society for information Management
• /
• v.24 no.1 s.63
• /
• pp.103-120
• /
• 2007

Node is the semantic unit and a part of structured document. Information retrieval from structured documents offers an opportunity to go subdivided below the document level in search of relevant information, making any element in an structured document a retrievable unit. The node-based document retrieval constitutes several similarity calculating methods and the extended node retrieval method using structure information. Retrieval performance is hardly influenced by the methods for determining document similarity The extended node method outperformed the others as a whole.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.7 no.5
• /
• pp.1252-1271
• /
• 2013

Automatic image annotation has become an increasingly important research topic owing to its key role in image retrieval. Simultaneously, it is highly challenging when facing to large-scale dataset with large variance. Practical approaches generally rely on similarity measures defined over images and multi-label prediction methods. More specifically, those approaches usually 1) leverage similarity measures predefined or learned by optimizing for ranking or annotation, which might be not adaptive enough to datasets; and 2) predict labels separately without taking the correlation of labels into account. In this paper, we propose a method for image annotation through collaborative similarity metric learning from dataset and modeling the label correlation of the dataset. The similarity metric is learned by simultaneously optimizing the 1) image ranking using structural SVM (SSVM), and 2) image annotation using correlated label propagation, with respect to the similarity metric. The learned similarity metric, fully exploiting the available information of datasets, would improve the two collaborative components, ranking and annotation, and sequentially the retrieval system itself. We evaluated the proposed method on Corel5k, Corel30k and EspGame databases. The results for annotation and retrieval show the competitive performance of the proposed method.

• Structural Engineering and Mechanics
• /
• v.17 no.3_4
• /
• pp.331-346
• /
• 2004

A new sensor system is proposed for measuring damage indexes. The damage index is a physical value that is well correlated to a critical damage in a device or a structure. The mechanism proposed here utilizes elastic buckling of a thin wire and does not require any external power supply for memorizing the index. The mechanisms to detect peak strain, peak displacement, peak acceleration and cumulative deformation as examples of damage indexes are presented. Furthermore, passive and active wireless data retrieval mechanisms using electromagnetic induction are proposed. The passive wireless system is achieved by forming a closed LC circuit to oscillate at its natural frequency. The active wireless sensor can transmit the data much further than the passive system at the sacrifice of slightly complicated electric circuit for the sensor. For wireless data retrieval, no wire is needed for the sensor to supply electrical power. For the active system, electrical power is supplied to the sensor by radio waves emitted from the retrieval system. Thus, external power supply is only needed for the retrieval system when the retrieval becomes necessary. Theoretical and experimental studies to show excellent performance of the proposed sensor are presented. Finally, a prototype damage index sensor installed into a 7 storey base-isolated building is explained.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.10 no.2
• /
• pp.396-406
• /
• 2009

In extension to our previous study, we develop metadata that specify elements' structural orders, to increase the efficiency level of XML document's retrieval process. Then, we proposed a structure-based indexing model. We expect the model to generate a more efficient retrieval process of horizontally and vertically related elements. To evaluate the model's performance level, we developed an experimental prototype and conducted an experiment on an XML corpus. On average, descendant, ancestor and sibling retrievals were approximately twelve percent faster than the ETID model. And retrievals specifying structural orders of particular element types were approximately twenty-five percent faster than the ETID model. In conclusion, metadata, such as Etype, Asso and Lsso, may make a meaningful contribution to retrieval processes that specify elements' order.

• Journal of Korean Association for Spatial Structures
• /
• v.7 no.6
• /
• pp.75-82
• /
• 2007

In this study, a design-supporting system, which is intended to assist engineers in the schematic phase of the structural design, is developed using a case database that contains design information of tall buildings in Korea. A case-based reasoning method utilizing the case database is proposed. The inductive retrieval module for selecting structural system, in the initial stage, from the design information of case database for 47 tall buildings is presented. Also, the nearest-neighbor retrieval method for selecting similar design cases is introduced.

• Journal of the Korea Society of Computer and Information
• /
• v.6 no.4
• /
• pp.85-93
• /
• 2001

As progressing rapidly to the information society and increasing greatly the amount of information, many researchers have been made utilizing XML to store and retrieval the information effectively. But, many other existing method could not support various structured retrieval method for specific parent, children and sibling nodes. In this paper, we propose (1)an effective method of representation for structured information and of indexing mechanism using OETID(Ordered Element Type ID) for effective management and structured retrieval of the XML documents. Also it contains another proposal that is (2) a documents integration mechanism for retrieval result and storing technique to store structural information of the XML documents. With our methods, we could effectively represent structural information of XML documents, and could directly access the specific elements and process various queries by simple operations.