• Title/Summary/Keyword: Contextual information

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A Study on the Factors Affecting the Intention to Use O2O Services (O2O 서비스의 사용의도에 영향을 미치는 요인에 관한 연구)

  • Jeong, Yu Jin;Song, Yong Uk
    • Journal of Information Technology Services
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    • v.15 no.4
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    • pp.125-151
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    • 2016
  • In recent years, O2O (Online to Offline) services get a lot of attention to improve the trust in online shopping and minimize the inconvenience and the cost burden in offline shopping as the number of consumers, who do not show concern about the purchase platform like online or offline, increases. Even though the services have been getting the spotlight as a strong business platform for next generation commerce, there have been only a few studies on the O2O services. The purpose of this research is to investigate the factors which affect the consumer's intention to use location-based O2O services. The study is based on VAM (Value-based Adoption Model) which is able to analyze those factors from the aspects of benefit and sacrifice. We used the partial least squares (PLS) method for empirical analysis, and the result shows that contextual offers, instant connectivity, webrooming and economic efficiency, which fall under the benefit, affect perceived value positively while annoyance and face consciousness, which fall under the sacrifice, do not affect perceived value significantly. In addition, contextual offers and instant connectivity affect trust positively. Location accuracy, which falls under the benefit of location-based O2O service, do not significantly affect perceived value and trust while security risk affects trust and use intention negatively. It appears that trust affects perceived value and use intention positively.

AN ABSTRACTION MODEL FOR IN-SITU SENSOR DATA USING SENSORML

  • Lee Yang Koo;Jung Young Jin;Park Mi;Kim Hak Cheol;Lee Chung Ho;Ryu Keun Ho
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.337-340
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    • 2005
  • Context-awareness techniques in ubiquitous computing environment provide various services to users who need to get information via the analysis of collected information from sensors in a spatial area. Context-awareness has been increased in ubiquitous computing and is applied to many different applications such as disaster management system, intelligent robot system, transportation management system, shopping management system, and digital home service. Many researches have recently focused on services that provide the appropriate information, which are collected from Internet by different kinds of sensors, to users according to context of their surrounding environment. In this paper, we propose an abstraction model to manage the large-scale contextual information and their metadata which are collected from different kinds of in-situ sensors in a spatial area and are presented them on the web. This model is composed of the modules expressing functional elements of sensors using sensorML(Sensor Model Language) based on XML language and the modules managing contextual information, which is transmitted from the sensors.

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An Investigation on Image Needs and Contexts in Image Search Failure (이미지 검색 실패에 나타난 이미지 요구와 맥락에 관한 분석)

  • Chung, EunKyung
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.26 no.1
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    • pp.199-215
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    • 2015
  • As a way of identifying users' image needs for improved effectiveness of image search, there have been recent research approaches to examine contextual factors in image needs with multiple perspectives. In this line of research, this study examined a total of 70 unsuccessful image searches for the purpose of investigating users' image needs. In order to achieve the purpose of this study, in particular, the characteristics of image needs, contextual factors on image needs, and image queries were investigated. The findings of this study demonstrated that information needs from the failed image searches are categorized primarily into specific and general/nameable categories. More importantly, these information needs are embedded with multiple contextual factors, primarily, task purpose and use purpose. With an analysis of detailed use purposes for image, illustration use was found most in this data set. For query analysis, the type of unique/refined image query was revealed primarily. As the results of this study were found similar to the findings of previous studies, it is possible to characterize the image needs from the failed image searches. In addition, the findings of this study are expected to be useful to the design and service of image retrieval.

A Music Recommendation Method Using Emotional States by Contextual Information

  • Kim, Dong-Joo;Lim, Kwon-Mook
    • Journal of the Korea Society of Computer and Information
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    • v.20 no.10
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    • pp.69-76
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    • 2015
  • User's selection of music is largely influenced by private tastes as well as emotional states, and it is the unconsciousness projection of user's emotion. Therefore, we think user's emotional states to be music itself. In this paper, we try to grasp user's emotional states from music selected by users at a specific context, and we analyze the correlation between its context and user's emotional state. To get emotional states out of music, the proposed method extracts emotional words as the representative of music from lyrics of user-selected music through morphological analysis, and learns weights of linear classifier for each emotional features of extracted words. Regularities learned by classifier are utilized to calculate predictive weights of virtual music using weights of music chosen by other users in context similar to active user's context. Finally, we propose a method to recommend some pieces of music relative to user's contexts and emotional states. Experimental results shows that the proposed method is more accurate than the traditional collaborative filtering method.

A Similarity Ranking Algorithm for Image Databases (이미지 데이터베이스 유사도 순위 매김 알고리즘)

  • Cha, Guang-Ho
    • Journal of KIISE:Databases
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    • v.36 no.5
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    • pp.366-373
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    • 2009
  • In this paper, we propose a similarity search algorithm for image databases. One of the central problems regarding content-based image retrieval (CBIR) is the semantic gap between the low-level features computed automatically from images and the human interpretation of image content. Many search algorithms used in CBIR have used the Minkowski metric (or $L_p$-norm) to measure similarity between image pairs. However those functions cannot adequately capture the aspects of the characteristics of the human visual system as well as the nonlinear relationships in contextual information. Our new search algorithm tackles this problem by employing new similarity measures and ranking strategies that reflect the nonlinearity of human perception and contextual information. Our search algorithm yields superior experimental results on a real handwritten digit image database and demonstrates its effectiveness.

A Bottom-up and Top-down Based Disparity Computation

  • Kim, Jung-Gu;hong Jeong
    • Journal of Electrical Engineering and information Science
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    • v.3 no.2
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    • pp.211-221
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    • 1998
  • It is becoming apparent that stereo matching algorithms need much information from high level cognitive processes. Otherwise, conventional algorithms based on bottom-up control alone are susceptible to local minima. We introduce a system that consists of two levels. A lower level, using a usual matching method, is based upon the local neighborhood and a second level, that can integrate the partial information, is aimed at contextual matching. Conceptually, the introduction of bottom-up and top-down feedback loop to the usual matching algorithm improves the overall performance. For this purpose, we model the image attributes using a Markov random field (MRF) and thereupon derive a maximum a posteriori (MAP) estimate. The energy equation, corresponding to the estimate, efficiently represents the natural constraints such as occlusion and the partial informations from the other levels. In addition to recognition, we derive a training method that can determine the system informations from the other levels. In addition to recognition, we derive a training method that can determine the system parameters automatically. As an experiment, we test the algorithms using random dot stereograms (RDS) as well as natural scenes. It is proven that the overall recognition error is drastically reduced by the introduction of contextual matching.

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Factors Affecting User Acceptance of Mobile Commerce Services

  • Jun, Jungho;Lee, Kyoung Jun;Kim, Byung Gon
    • Asia pacific journal of information systems
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    • v.26 no.4
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    • pp.489-508
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    • 2016
  • Growth in the use of mobile commerce services (MCS) as an enabler to conduct business more effectively has been phenomenal. Technology acceptance model (TAM) has been applied in different contexts to examine a wide range of information technology. As more and more companies are finding ways to utilize MCS, an important issue is to understand what factors will affect the decisions of consumers in adopting the services. Based on TAM with two additional groups of external factors (i.e., service-related factors [ubiquitous access and contextual service] and technology-related factors [perceived security risk and network connectivity]) that are theoretically justified to affect both perceived usefulness and perceived ease of use, which are also considered, a research model for the investigated technology acceptance was developed and empirically examined. The major results of this study are as follows. First, ubiquitous access affects perceived usefulness and perceived ease of use. Contextual service affects perceived usefulness. Second, perceived security risk affects perceived usefulness and perceived ease of use. Finally, network connectivity affects perceived usefulness and perceived ease of use.

Error Correction in Korean Morpheme Recovery using Deep Learning (딥 러닝을 이용한 한국어 형태소의 원형 복원 오류 수정)

  • Hwang, Hyunsun;Lee, Changki
    • Journal of KIISE
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    • v.42 no.11
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    • pp.1452-1458
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    • 2015
  • Korean Morphological Analysis is a difficult process. Because Korean is an agglutinative language, one of the most important processes in Morphological Analysis is Morpheme Recovery. There are some methods using Heuristic rules and Pre-Analyzed Partial Words that were examined for this process. These methods have performance limits as a result of not using contextual information. In this study, we built a Korean morpheme recovery system using deep learning, and this system used word embedding for the utilization of contextual information. In '들/VV' and '듣/VV' morpheme recovery, the system showed 97.97% accuracy, a better performance than with SVM(Support Vector Machine) which showed 96.22% accuracy.

A Study of Students' Mathematical Context Information Accompanied Problem -Solving Activities (수학적 맥락 정보를 이용한 수업 환경에서의 학습자의 문제 해결 활동)

  • Bae Min Jeong;Paik Suk-Yoon
    • Journal of Elementary Mathematics Education in Korea
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    • v.7 no.1
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    • pp.23-44
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    • 2003
  • The purpose of the study is to examine the phenomenon presented the process of problem solving activities of students with the mathematical context information accompanied problem based on Freudenthal's mathematizing theory and Realistic Mathematics Educations about cognitive and emotional aspects. In conclusion, taking a look at the results of study, open-ended contextual problem was had to offer in order to pull out various solutions. Teachers should help students develop their own methods, discuss their methods with others' and reinvent formal mathematics and its constructive process under the guidance of the teachers.

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An Analytical Interpretation of Cultural Resources in Terms of Digital Archiving (디지털 아카이빙으로서의 문화자원에 대한 해석)

  • Chung, Jun-Min
    • Journal of the Korean Society for information Management
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    • v.27 no.2
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    • pp.217-224
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    • 2010
  • This paper starts with the question, what are culture and cultural resources? The meanings of cultural resources are mentioned historically and archaeologically. The culture dynamic is introduced and the cultural resources are interpreted as processes and practices along with which culture is produced and reproduced through the action of individual. Digital archiving concluds that the cultural resources are only meaningful when they are archived with their contexts and processes. Finally paper induces that cultural archives could be valuable, when they are preserved (synthetic), recognized (contextual) and enjoyed (exhibited, experienced or practically used).