Skip to main content

MobEx: A System for Exploratory Search on the Mobile Web

  • Conference paper
  • 839 Accesses

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 358))

Abstract

We present MobEx, a mobile touchable application for exploratory search on the mobile web. The system has been implemented for operation on a tablet computer, i.e. an Apple iPad, and on a mobile device, i.e. Apple iPhone or iPod touch. Starting from a topic issued by the user the system collects web snippets that have been determined by a standard search engine in a first step and extracts associated topics to the initial query in an unsupervised way on-demand and highly performant. This process is recursive in priciple as it furthermore determines other topics associated to the newly found ones and so forth. As a result MobEx creates a dense web of associated topics that is presented to the user as an interactive topic graph. We consider the extraction of topics as a specific empirical collocation extraction task where collocations are extracted between chunks combined with the cluster descriptions of an online clustering algorithm. Our measure of association strength is based on the pointwise mutual information between chunk pairs which explicitly takes their distance into account. These syntactically–oriented chunk pairs are then semantically ranked and filtered using the cluster descriptions created by a Singular Value Decomposition (SVD) approach. An initial user evaluation shows that this system is especially helpful for finding new interesting information on topics about which the user has only a vague idea or even no idea at all.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Banko, M., Cafarella, M.J., Soderland, S., Broadhead, M., Etzioni, O.: Open information extraction from the web. In: Proceedings of IJCAI 2007, pp. 2670–2676 (2007)

    Google Scholar 

  2. Baroni, M., Evert, S.: Statistical methods for corpus exploitation. In: Lüdeling, A., Kytö, M. (eds.) Corpus Linguistics. An International Handbook. Mouton de Gruyter, Berlin (2008)

    Google Scholar 

  3. Dingare, S., Nissim, M., Finkel, J., Grover, C., Manning, C.D.: A system for identifying named entities in biomedical text: How results from two evaluations reflect on both the system and the evaluations. Comparative and Functional Genomics 6, 77–85 (2004)

    Article  Google Scholar 

  4. Drozdzynski, W., Krieger, H.-U., Piskorski, J., Schäfer, U., Xu, F.: Shallow processing with unification and typed feature structures — foundations and applications. Künstliche Intelligenz, 17–23 (2004)

    Google Scholar 

  5. Etzioni, O.: Machine reading of web text. In: Proceedings of the 4th International Conference on Knowledge Capture, Whistler, BC, Canada, pp. 1–4 (2007)

    Google Scholar 

  6. Geraci, F., Pellegrini, M., Maggini, M., Sebastiani, F.: Cluster generation and labeling for web snippets: A fast, accurate hierarchical solution. Journal of Internet Mathematics 4(4), 413–443 (2006)

    Article  MathSciNet  Google Scholar 

  7. Giesbrecht, E., Evert, S.: Part-of-speech tagging - a solved task? an evaluation of pos taggers for the web as corpus. In: Proceedings of the 5th Web as Corpus Workshop (2009)

    Google Scholar 

  8. Gimenez, J., Marquez., L.: Svmtool: A general pos tagger generator based on support vector machines. In: Proceedings of LREC 2004, pp. 43–46 (2004)

    Google Scholar 

  9. Manning, C.D., Raghavan, P., Schütze, H.: Introduction to information retrieval. Cambridge University Press (2008)

    Google Scholar 

  10. Marchionini, G.: Exploratory search: from finding to understanding. Commun. ACM 49(4), 41–46 (2006)

    Article  Google Scholar 

  11. Nadeau, D., Sekine, S.: A survey of named entity recognition and classification. Journal of Linguisticae Investigationes 30(1), 1–20 (2007)

    Article  Google Scholar 

  12. Neumann, G., Schmeier, S.: A mobile touchable application for online topic graph extraction and exploration of web content. In: Proceedings of the ACL-HLT 2011 System Demonstrations (2011)

    Google Scholar 

  13. Osinski, S., Stefanowski, J., Weiss, D.: Lingo: Search results clustering algorithm based on singular value decomposition. In: Proceedings of the International IIS: Intelligent Information Processing and Web Mining Conference. Springer (2004)

    Google Scholar 

  14. Osinski, S., Weiss, D.: Carrot2: Making sense of the haystack. In: ERCIM News (2008)

    Google Scholar 

  15. Turney, P.D.: Mining the Web for Synonyms: PMI-IR versus LSA on TOEFL. In: Flach, P.A., De Raedt, L. (eds.) ECML 2001. LNCS (LNAI), vol. 2167, pp. 491–502. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  16. Yates, A.: Information extraction from the web: Techniques and applications. Ph.D. Thesis, University of Washington, Computer Science and Engineering (2007)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Neumann, G., Schmeier, S. (2013). MobEx: A System for Exploratory Search on the Mobile Web. In: Filipe, J., Fred, A. (eds) Agents and Artificial Intelligence. ICAART 2012. Communications in Computer and Information Science, vol 358. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36907-0_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-36907-0_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-36906-3

  • Online ISBN: 978-3-642-36907-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics