Skip to main content

ABC Algorithm for URL Extraction

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10544))

Abstract

Seed URLs, Content Classification, Indexing and Ranking are key factors for search results relevance. Domain specific search engines (DSSE) provide more relevant search results as they have lesser ambiguity issues. For wide usage of DSSEs, identification of seed URLs and related child URLs is required. Identification of seed URLs has been manual and takes longer duration for building/decisioning on URL availability for DSSE. We propose nature inspired Artificial Bee Colony algorithm for identification and scoring of seed and child URLs. We implemented the algorithm on ‘Security’ domain and extracted 34,007 seed URLs from Wikipedia data dump and 323,488 child URLs using the seed URLs. Based on the volume and the relevance of the extracted URLs, a decision for building a DSSE can be made easily.

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 EPUB and 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

Notes

  1. 1.

    http://www.algorithmsinnature.org/.

  2. 2.

    https://github.com/souravsarangi/SeedURLWork.

  3. 3.

    http://tinyurl.com/URLData.

  4. 4.

    https://radimrehurek.com/gensim/models/phrases.html.

References

  1. Ahmadi-Abkenari, F., Selamat, A.: An architecture for a focused trend parallel web crawler with the application of clickstream analysis. Inf. Sci. 184(1), 266–281 (2012)

    Article  Google Scholar 

  2. Chakrabarti, S., Punera, K., Subramanyam, M.: Accelerated focused crawling through online relevance feedback. In: Proceedings of the 11th International Conference on World Wide Web, pp. 148–159. ACM (2002)

    Google Scholar 

  3. Diligenti, M., Coetzee, F., Lawrence, S., Giles, C.L., Gori, M., et al.: Focused crawling using context graphs. In: VLDB, pp. 527–534 (2000)

    Google Scholar 

  4. Du, Y., Hai, Y., Xie, C., Wang, X.: An approach for selecting seed urls of focused crawler based on user-interest ontology. Appl. Soft Comput. 14, 663–676 (2014)

    Article  Google Scholar 

  5. Frank, E., Paynter, G.W., Witten, I.H., Gutwin, C., Nevill-Manning, C.G.: Domain-specific keyphrase extraction. In: 16th International Joint Conference on Artificial Intelligence (IJCAI 99), vol. 2, pp. 668–673. Morgan Kaufmann Publishers Inc., San Francisco (1999)

    Google Scholar 

  6. Karaboga, D., Akay, B.: A comparative study of artificial bee colony algorithm. Appl. Math. Comput. 214(1), 108–132 (2009)

    MathSciNet  MATH  Google Scholar 

  7. Karaboga, D., Akay, B.: A survey: Algorithms simulating bee swarm intelligence. Artif. Intell. Rev. 31(1–4), 61–85 (2009)

    Article  Google Scholar 

  8. Karaboga, D., Gorkemli, B., Ozturk, C., Karaboga, N.: A comprehensive survey: artificial bee colony (abc) algorithm and applications. Artif. Intell. Rev. 42(1), 21–57 (2014)

    Article  Google Scholar 

  9. McCallum, A., Nigam, K., Rennie, J., Seymore, K.: A machine learning approach to building domain-specific search engines. In: IJCAI, vol. 99, pp. 662–667. Citeseer (1999)

    Google Scholar 

  10. Najork, M.: Web crawler architecture. In: Encyclopedia of Database Systems, pp. 3462–3465. Springer (2009)

    Google Scholar 

  11. Pappas, N., Katsimpras, G., Stamatatos, E.: An agent-based focused crawling framework for topic-and genre-related web document discovery. In: IEEE 24th International Conference on Tools with Artificial Intelligence, vol. 1, pp. 508–515. IEEE (2012)

    Google Scholar 

  12. Zheng, S., Dmitriev, P., Giles, C.L.: Graph-based seed selection for web-scale crawlers. In: Proceedings of the 18th ACM Conference on Information and Knowledge Management, pp. 1967–1970. ACM (2009)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Lalit Mohan Sanagavarapu .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Sanagavarapu, L.M., Sarangi, S., Reddy, Y.R. (2018). ABC Algorithm for URL Extraction. In: Garrigós, I., Wimmer, M. (eds) Current Trends in Web Engineering. ICWE 2017. Lecture Notes in Computer Science(), vol 10544. Springer, Cham. https://doi.org/10.1007/978-3-319-74433-9_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-74433-9_12

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-74432-2

  • Online ISBN: 978-3-319-74433-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics