• Title/Summary/Keyword: Paid Search Advertising

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To Bid or Not to Bid? - Keyword Selection in Paid Search Advertising

  • Ma, Yingying;Sun, Luping
    • Asia Marketing Journal
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    • v.16 no.3
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    • pp.23-33
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    • 2014
  • The selection of keywords for bidding is a critical component of paid search advertising. When the number of possible keywords is enormous, it becomes difficult to choose the best keywords for advertising and then subsequently to assess their effect. To this end, we propose an ultrahigh dimensional keyword selection approach that not only reduces the dimension for selections, but also generates the top listed keywords for profits. An empirical analysis using a unique panel dataset from a large online clothes retailer that advertises on the largest search engine in China (i.e., Baidu) is presented to illustrate the usefulness of our approach.

Generation of AI Agent in Imperfect Information Card Games Using MCTS Algorithm: Focused on Hearthstone (MCTS 기법을 활용한 불완전 정보 카드 게임에서의 인공지능 에이전트 생성 : 하스스톤을 중심으로)

  • Oh, Pyeong;Kim, Ji-Min;Kim, Sun-Jeong;Hong, Seokmin
    • Journal of Korea Game Society
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    • v.16 no.6
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    • pp.79-90
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    • 2016
  • Recently, many researchers have paid attention to the improved generation of AI agent in the area of game industry. Monte-Carlo Tree Search(MCTS) is one of the algorithms to search an optimal solution through random search with perfect information, and it is suitable for the purpose of calculating an approximate value to the solution of an equation which cannot be expressed explicitly. Games in Trading Card Game(TCG) genre such as the heartstone has imperfect information because the cards and play of an opponent are not predictable. In this study, MCTS is suggested in imperfect information card games so as to generate AI agents. In addition, the practicality of MCTS algorithm is verified by applying to heartstone game which is currently used.

Automatic Map Generation without an Isolated Cave Using Cell Automata Enhanced by Binary Space Partitioning (이진 공간 분할로 보강된 셀 오토마타를 이용한 고립 동굴 없는 맵 자동 생성)

  • Kim, Ji-Min;Oh, Pyeong;Kim, Sun-Jeong;Hong, Seokmin
    • Journal of Korea Game Society
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    • v.16 no.6
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    • pp.59-68
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    • 2016
  • Many researchers have paid attention to contents generation within the area of game artificial intelligence these days with various reasons. Efforts on automatic contents generation without game level designers' help were continuously progressed in various game contents. This study suggests an automatic map generation without an isolated cave using cellular automation enhanced by binary space partitioning(BSP). In other words, BSP makes it possible to specify the number of desired area and cellular automation reduces the time to search a path. Based upon our preliminary simulation results, we show the usefulness of our automatic map generation by applying the contents generation using cell automation, which is enhanced by BSP to games.