ARES: A Retrieval Engine Based on Sentiments

Sentiment-Based Search Result Annotation and Diversification
  • Gianluca Demartini
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6611)


This paper introduces a system enriching the standard web search engine interface with sentiment information. Additionally, it exploits such annotations to diversify the result list based on the different sentiments expressed by retrieved web pages. Thanks to the annotations, the end user is aware of which opinions the search engine is showing her and, thanks to the diversification, she can see an overview of the different opinions expressed about the requested topic. We describe the methods used for computing sentiment scores of web search results and for re-ranking them in order to cover different sentiment classes. The proposed system, built on top of commercial search engine APIs, is available on-line.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Demartini, G., Siersdorfer, S.: Dear Search Engine: What’s your opinion about...? - Sentiment Analysis for Semantic Enrichment of Web Search Results. In: Semantic Search 2010 Workshop located at the 19th Int. World Wide Web Conference WWW 2010 (2010)Google Scholar
  2. 2.
    Esuli, A., Sebastiani, F.: SENTIWORDNET: A publicly available lexical resource for opinion mining. In: In Proceedings of the 5th Conference on Language Resources and Evaluation (LREC 2006), pp. 417–422 (2006)Google Scholar
  3. 3.
    Kohlschütter, C., Fankhauser, P., Nejdl, W.: Boilerplate detection using shallow text features. In: WSDM, pp. 441–450 (2010)Google Scholar
  4. 4.
    Macdonald, C., Santos, R.L.T., Ounis, I., Soboroff, I.: Blog track research at trec. SIGIR Forum 44(1), 58–75 (2010)CrossRefGoogle Scholar
  5. 5.
    Ounis, I., Macdonald, C., Soboroff, I.: Overview of the TREC 2008 Blog Track. In: TREC (2008)Google Scholar
  6. 6.
    Santos, R.L.T., Macdonald, C., Ounis, I.: Exploiting query reformulations for web search result diversification. In: WWW, pp. 881–890 (2010)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Gianluca Demartini
    • 1
  1. 1.L3S Research CenterHannoverGermany

Personalised recommendations