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Feature Extraction and Summarization of Recipes Using Flow Graph

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Social Informatics (SocInfo 2013)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8238))

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Abstract

These days, there are more than a million recipes on the Web. When you search for a recipe with one query such as “nikujaga,” the name of a typical Japanese food, you can find thousands of “nikujaga” recipes as the result. Even if you focus on only the top ten results, it is still difficult to find out the characteristic feature of each recipe because a cooking is a work-flow including parallel procedures. According to our survey, people place the most importance on the differences of cooking procedures when they compare the recipes. However, such differences are difficult to be extracted just by comparing the recipe texts as existing methods. Therefore, our system extracts (i) a general way to cook as a summary of cooking procedures and (ii) the characteristic features of each recipe by analyzing the work-flows of the top ten results. In the experiments, our method succeeded in extracting 54% of manually extracted features while the previous research addressed 37% of them.

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Author information

Authors and Affiliations

  1. Graduate School of Informatics, Kyoto University, Yoshida-Honmachi, Sakyo-ku, Kyoto, 606-8501, Japan

    Yoko Yamakata, Yuichi Sugiyama & Katsumi Tanaka

  2. Graduate School of Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, 464-8603, Japan

    Shinji Imahori

  3. Academic Center for Computing and Media Studies, Kyoto University, Yoshida-Honmachi, Sakyo-ku, Kyoto, 606-8501, Japan

    Shinsuke Mori

Authors
  1. Yoko Yamakata
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  2. Shinji Imahori
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  3. Yuichi Sugiyama
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  4. Shinsuke Mori
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  5. Katsumi Tanaka
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Editor information

Editors and Affiliations

  1. Department of Social Informatics, Graduate School of Informatics, Kyoto University, Yoshida-Honmachi, 606-8501, Sakyo-ku, Kyoto, Japan

    Adam Jatowt

  2. School of Information Systems, Singapore Management University, 80 Stamford Road, 178902, Singapore

    Ee-Peng Lim  & Bing Tian Dai  & 

  3. Department of Information and Library Science, School of Informatics and Computing, Indiana University, 1320 E. 10th St., LI 011, 47405, Bloomington, IN, USA

    Ying Ding

  4. Department of Integrated Psychological Sciences, Kwansei Gakuin University, 1-1-155 Uegahara, 662-8501, Nishinomiya, Hyogo, Japan

    Asako Miura

  5. Faculty of Library, Information and Media Science, University of Tsukuba, 1-2 Kasuga, 305-8550, Tsukuba City, Ibaraki, Japan

    Taro Tezuka

  6. Department of Computer Science, University of Caen Basse-Normandie, Campus Côte de Nacre, F-14032, Caen Cedex, France

    Gaël Dias

  7. Department of Social Informatics, Graduate School of Informatics,, Kyoto University, 606-8501, Kyoto, Japan

    Katsumi Tanaka

  8. Department of Communication, University of California, 93106, Santa Barbara, CA, USA

    Andrew Flanagin

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© 2013 Springer International Publishing Switzerland

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Yamakata, Y., Imahori, S., Sugiyama, Y., Mori, S., Tanaka, K. (2013). Feature Extraction and Summarization of Recipes Using Flow Graph. In: Jatowt, A., et al. Social Informatics. SocInfo 2013. Lecture Notes in Computer Science, vol 8238. Springer, Cham. https://doi.org/10.1007/978-3-319-03260-3_21

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  • DOI: https://doi.org/10.1007/978-3-319-03260-3_21

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-03259-7

  • Online ISBN: 978-3-319-03260-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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