• Title/Summary/Keyword: Image Search Engine

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An analysis of user behaviors on the search engine results pages based on the demographic characteristics

  • Bitirim, Yiltan;Ertugrul, Duygu Celik
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.7
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    • pp.2840-2861
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    • 2020
  • The purpose of this survey-based study is to make an analysis of search engine users' behaviors on the Search Engine Results Pages (SERPs) based on the three demographic characteristics gender, age, and program studying. In this study, a questionnaire was designed with 12 closed-ended questions. Remaining questions other than the demographic characteristic related ones were about "tab", "advertisement", "spelling suggestion", "related query suggestion", "instant search suggestion", "video result", "image result", "pagination" and the amount of clicking results. The questionnaire was used and the data collected were analyzed with the descriptive statistics as well as the inferential statistics. 84.2% of the study population was reached. Some of the major results are as follows: Most of each demographic characteristic category (i.e. female, male, under-20, 20-24, above-24, English computer engineering, Turkish computer engineering, software engineering) have rarely or more click for tab, spelling suggestion, related query suggestion, instant search suggestion, video result, image result, and pagination. More than 50.0% of female category click advertisement rarely; however, for the others, 50.0% or more never click advertisement. For every demographic characteristic category, between 78.0% and 85.4% click 10 or fewer results. This study would be the first attempt with its complete content and design. Search engine providers and researchers would gain knowledge to user behaviors about the usage of the SERPs based on the demographic characteristics.

The Effects of Product Image Locations and Product Type on Responses to Search Engine Advertising (제품검색광고 내 제품 이미지 위치와 판매 단위 유형이 광고효과에 미치는 영향에 대한 연구)

  • Lee, Sungmi
    • Journal of Digital Convergence
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    • v.19 no.12
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    • pp.397-404
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    • 2021
  • Product image location in search engine advertising plays an important role in consumer perception when the product is relatively low involved and has functional value. The purpose of this research is to investigate the interaction effects of product image location and product type on advertising effectiveness. Building on the literature of location effects, we show that for products for which heaviness is considered a positive attribute, product image placed on the right are preferred. To test hypotheses, a 2(product image location: left vs. right) × 2(product type: single vs. bundle) experiment is conducted and a total of 144 paricipants took part in the experiment. The results revealed that respondents show higher brand attitude and purchse intention toward a bundle product's advertising with product image place on the right. The results provide implications and suggestions for improving search engine advertising and marketing strategies.

Implementation of Annotation and Thesaurus for Remote Sensing

  • Chae, Gee-Ju;Yun, Young-Bo;Park, Jong-Hyun
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.222-224
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    • 2003
  • Many users want to add some their own information to data which was on the web and computer without actually needing to touch data. In remote sensing, the result data for image classification consist of image and text file in general. To overcome these inconvenience problems, we suggest the annotation method using XML language. We give the efficient annotation method which can be applied to web and viewing of image classification. We can apply the annotation for web and image classification with image and text file. The need for thesaurus construction is the lack of information for remote sensing and GIS on search engine like Empas, Naver and Google. In search engine, we can’t search the information for word which has many different names simultaneously. We select the remote sensing data from different sources and make the relation between many terms. For this process, we analyze the meaning for different terms which has similar meaning.

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Realization for Image Searching Engine with Moving Object Identification and Classification

  • Jung, Eun-Suk;Ryu, Kwang-Ryol;Sclabassi, Robert J.
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2007.10a
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    • pp.301-304
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    • 2007
  • A realization for image searching engine with moving objects identification and classification is presented in this paper. The identification algorithm is applied to extract difference image between input image and the reference image, and the classification is used the region segmentation. That is made the database for the searching engine. The experimental result of the realized system enables to search for human and animal at time intervals to use a surveillant system at inside environment.

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An Efficient Comparing and Updating Method of Rights Management Information for Integrated Public Domain Image Search Engine

  • Kim, Il-Hwan;Hong, Deok-Gi;Kim, Jae-Keun;Kim, Young-Mo;Kim, Seok-Yoon
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.1
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    • pp.57-65
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    • 2019
  • In this paper, we propose a Rights Management Information(RMI) expression systems for individual sites are integrated and the performance evaluation is performed to find out an efficient comparing and updating method of RMI through various image feature point search techniques. In addition, we proposed a weighted scoring model for both public domain sites and posts in order to use the most latest RMI based on reliable data. To solve problem that most public domain sites are exposed to copyright infringement by providing inconsistent RMI(Rights Management Information) expression system and non-up-to-date RMI information. The weighted scoring model proposed in this paper makes it possible to use the latest RMI for duplicated images that have been verified through the performance evaluation experiments of SIFT and CNN techniques and to improve the accuracy when applied to search engines. In addition, there is an advantage in providing users with accurate original public domain images and their RMI from the search engine even when some modified public domain images are searched by users.

Categorizing Web Image Search Results Using Emotional Concepts (감성 개념을 이용한 웹 이미지 검색 결과 분류)

  • Kim, Young-Rae;Kwon, Kyung-Su;Shin, Yun-Hee;Kim, Eun-Yi
    • 한국HCI학회:학술대회논문집
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    • 2009.02a
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    • pp.562-566
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    • 2009
  • In this paper, we present a novel system to categorize web image search results using emotional concepts and to browse the results more conveniently and easily. The proposed system can categorize search results into 8 emotional categories based on emotion vector, which obtained by color and pattern features. Here, we use Kobayashi’s emotional categories: {romantic, natural, casual, elegant, chic, classic, dandy and modern}. With search results for a given query, the proposed system can provide categorized images for each emotional category. With 1,000 Yahoo! search images, we compared the proposed method with Yahoo! image search engine in respect of satisfaction, efficiency, convenience and relevance with a user study. Our experimental results show the effectiveness of the proposed method.

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Semantic Image Search: Case Study for Western Region Tourism in Thailand

  • Chantrapornchai, Chantana;Bunlaw, Netnapa;Choksuchat, Chidchanok
    • Journal of Information Processing Systems
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    • v.14 no.5
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    • pp.1195-1214
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    • 2018
  • Typical search engines may not be the most efficient means of returning images in accordance with user requirements. With the help of semantic web technology, it is possible to search through images more precisely in any required domain, because the images are annotated according to a custom-built ontology. With appropriate annotations, a search can then, return images according to the context. This paper reports on the design of a tourism ontology relevant to touristic images. In particular, the image features and the meaning of the images are described using various properties, along with other types of information relevant to tourist attractions using the OWL language. The methodology used is described, commencing with building an image and tourism corpus, creating the ontology, and developing the search engine. The system was tested through a case study involving the western region of Thailand. The user can search specifying the specific class of image or they can use text-based searches. The results are ranked using weighted scores based on kinds of properties. The precision and recall of the prototype system was measured to show its efficiency. User satisfaction was also evaluated, was also performed and was found to be high.

An Implementation of Search System based on Natural Language Index Incorporating considering Image Characteristics (이미지 특성을 고려한 자연어 색인 기반의 검색시스템 구현)

  • Kim, Jung-Yee;Lee, Ki-Wook;Lee, Kang-Ho
    • Journal of the Korea Society of Computer and Information
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    • v.11 no.5 s.43
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    • pp.337-343
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    • 2006
  • The number of digital camera users is increasing rapidly and countless number of photos floats about on the internet especially through wide-spreading Cyworld and blogs. Though portraits cover a large percentage of those photos, because of the property rights, near entirety or such photos are unavailable for use by web-page producers, advertising companies, web-designers, and so on, who need a variety of portraits with differing expressions and characteristics. This study offers a search engine that incorporates image characteristics based on natural language index, which can provide a fast and reliable search result. It will create an opportunity for the digital photographers to mure easily sell their pictures and simultaneously provide the would-be users of the photos a better and easier way to find the pictures they are looking for. Once the search engine is realized, it will become possible to use not only the nouns as keywords and categories but also verbs in search of portraits revealing feelings, expressions, dressings, and other characteristics.

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Image Classification Approach for Improving CBIR System Performance (콘텐트 기반의 이미지검색을 위한 분류기 접근방법)

  • Han, Woo-Jin;Sohn, Kyung-Ah
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.41 no.7
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    • pp.816-822
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    • 2016
  • Content-Based image retrieval is a method to search by image features such as local color, texture, and other image content information, which is different from conventional tag or labeled text-based searching. In real life data, the number of images having tags or labels is relatively small, so it is hard to search the relevant images with text-based approach. Existing image search method only based on image feature similarity has limited performance and does not ensure that the results are what the user expected. In this study, we propose and validate a machine learning based approach to improve the performance of the image search engine. We note that when users search relevant images with a query image, they would expect the retrieved images belong to the same category as that of the query. Image classification method is combined with the traditional image feature similarity method. The proposed method is extensively validated on a public PASCAL VOC dataset consisting of 11,530 images from 20 categories.

Comparison and Evaluation of Web-based Image Search Engines (이미지정보 탐색을 위한 웹 검색엔진의 비교 평가)

  • Kim, Hyo-Jung
    • Journal of Information Management
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    • v.31 no.4
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    • pp.50-70
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    • 2000
  • Since the contents of internet resources are beginning to include texts, images and sounds, different Web-based image search engines have been developed accordingly. It is a fact that these diversities of multimedia contents have made search process and retrieval of relevant information very difficult. The purpose of the study is to compare and evaluate its special features and performance of the existing image search engines in order to provide user help to select appropriate search engines. The study selected AV Photo Finder, Lycos MultiMedia, Amazing Picture Machine, Image Surfer, WebSeek, Ditto for comparison and evaluation because of their reputations of popularity among users of image search engines. The methodology of the study was to analyze previous related literature and establish criteria for the evaluation of image search engines. The study investigated characteristics, indexing methods, search capabilities, screen display and user interfaces of different search engines for the purpose of comparison of its performance. Finally, the study measured relative recall and precision ratios to evaluate their electiveness of retrieval under the experimental set up. Results of the comparative analysis in regard to its search performance are as follows. AV Photo Finder marked the highest rank among other image search engines. Ditto and WebSeek also showed comparatively high precision ratio. Lycos MultiMedia and Image Surfer follows after them. Amazing Picture Machine stowed the lowest in ranking.

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