• Title/Summary/Keyword: Bot Store

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(ro)Bot as media An experimental discussion on news chatbot (미디어로서의 봇(bot) 뉴스 챗봇에 대한 시론적 논의)

  • Oh, Se Wook
    • Korean journal of communication and information
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    • v.79
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    • pp.70-103
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    • 2016
  • In the face of crisis in the news media industry, many people prospect that new technology can save it. But there is no discussion about how new technology works and what is its limitations and which direction of development is needed. In view of media, this article analyzed 'news chatbot' as new technology. Firstly, this article defined bot and discussed bot's agency based on actor network theory. Secondly, it analysed bots which are acting as media and discussed features of the messenger platform as a communication tool. Thirdly, it presents examples of news chatbot and analyzed how they work. Finally, it predicts the future of news chatbot and discussed the possibility of journalism.

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MORPHEUS: A More Scalable Comparison-Shopping Agent (MORPHEUS: 확장성이 있는 비교 쇼핑 에이전트)

  • Yang, Jae-Yeong;Kim, Tae-Hyeong;Choe, Jung-Min
    • Journal of KIISE:Software and Applications
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    • v.28 no.2
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    • pp.179-191
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    • 2001
  • Comparison shopping is a merchant brokering process that finds the best price for the desired product from several Web-based online stores. To get a scalable comparison shopper, we need an agent that automatically constructs a simple information extraction procedure, called a wrapper, for each semi-structured store. Automatic construction of wrappers for HTML-based Web stores is difficult because HTML only defines how information is to be displayed, not what it means, and different stores employ different ways of manipulating customer queries and different presentation formats for displaying product descriptions. Wrapper induction has been suggested as a promising strategy for overcoming this heterogeneity. However, previous scalable comparison-shoppers such as ShopBot rely on a strong bias in the product descriptions, and as a result, many stores that do not confirm to this bias were unable to be recognized. This paper proposes a more scalable comparison-shopping agent named MORPHEUS. MORPHEUS presents a simple but robust inductive learning algorithm that antomatically constructs wrappers. The main idea of the proposed algorithm is to recognize the position and the structure of a product description unit by finding the most frequent pattern from the sequence of logical line information in output HTML pages. MORPHEUS successfully constructs correct wtappers for most stores by weakening a bias assumed in previous systems. It also tolerates some noises that might be present in production descriptions such as missing attributes. MORPHEUS generates the wrappers rapidly by excluding the pre-processing phase of removing redundant fragments in a page such as a header, a tailer, and advertisements. Eventually, MORPHEUS provides a framework from which a customized comparison-shopping agent can be organized for a user by facilitating the dynamic addition of new stores.

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