Summary of the paper

Title Subtask Mining from Search Query Logs for How-Knowledge Acceleration
Authors Chung-Lun Kuo and Hsin-Hsi Chen
Abstract "How-knowledge is indispensable in daily life, but has relatively less quantity and poorer quality than what-knowledge in publicly available knowledge bases. This paper first extracts task-subtask pairs from wikiHow, then mines linguistic patterns from search query logs, and finally applies the mined patterns to extract subtasks to complete given how-to tasks. To evaluate the proposed methodology, we group tasks and the corresponding recommended subtasks into pairs, and evaluate the results automatically and manually. The automatic evaluation shows the accuracy of 0.4494. We also classify the mined patterns based on prepositions and find that the prepositions like ""on"", ""to"", and ""with"" have the better performance. The results can be used to accelerate how-knowledge base construction."
Topics Knowledge Discovery/Representation, Information Extraction, Information Retrieval, Acquisition
Full paper Subtask Mining from Search Query Logs for How-Knowledge Acceleration
Bibtex @InProceedings{KUO16.663,
  author = {Chung-Lun Kuo and Hsin-Hsi Chen},
  title = {Subtask Mining from Search Query Logs for How-Knowledge Acceleration},
  booktitle = {Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)},
  year = {2016},
  month = {may},
  date = {23-28},
  location = {Portoro┼ż, Slovenia},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Sara Goggi and Marko Grobelnik and Bente Maegaard and Joseph Mariani and Helene Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  address = {Paris, France},
  isbn = {978-2-9517408-9-1},
  language = {english}
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