Answering Search Queries with CrowdSearcher: a crowdsourcing and social network approach to search

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Web users are increasingly relying on social interaction to complete and validate the results of their search activities. While search systems are superior machines to get world-wide information, the opinions collected within friends and expert/local communities can ultimately determine our decisions: human curiosity and creativity is often capable of going much beyond the capabilities of search systems in scouting “interesting” results, or suggesting new, unexpected search directions. Such personalized interaction occurs in most times aside of the search systems and processes, possibly instrumented and mediated by a social network; when such interaction is completed and users resort to the use of search systems, they do it through new queries, loosely related to the previous search or to the social interaction.
In this paper we propose CrowdSearcher, a novel search paradigm that embodies crowds as first-class sources for the information seeking process. CrowdSearcher aims at filling the gap between generalized search systems, which operate upon world-wide information - including facts and recommendations as crawled and indexed by computerized systems – with social systems, capable of interacting with real people, in real time, to capture their opinions, suggestions, emotions. The technical contribution of this paper is the discussion of a model and architecture for integrating computerized search with human interaction, by showing how search systems can drive and encapsulate social systems. In particular we show how social platforms, such as Facebook, LinkedIn and Twitter, can be used for crowdsourcing search-related tasks; we demonstrate our approach with several prototypes and we report on our experiment upon real user communities.

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Answering Search Queries with CrowdSearcher: a crowdsourcing and social network approach to search

  1. 1. Politecnico Di Milano Dipartimento Di Elettronica e Informazione Answering Search Queries with CrowdSearcher A crowdsourcing approach to searchAlessandro Bozzon, Marco Brambilla, Stefano CeriWWW 2012, Lyon, FranceApril, 20th 2012
  2. 2. Context• Web is a huge, heterogeneous data source: • Structured, unstructured and semi-structured data • Known problems of trust, reputation, consistency• User needs to solve real-life problems, not to find a web site Answering Search Queries with CrowdSearcher
  3. 3. Context Answering Search Queries with CrowdSearcher
  4. 4. Context• User needs to solve real-life problems, not to find a web site • Web queries get increasingly complex and specialized • Exploratory search • From document search to object search• Search as a service • Viability of systems based upon search service orchestration Answering Search Queries with CrowdSearcher
  5. 5. Background: semantic multi-domain search“… search for upcoming concerts close to an attractive location (like a beach, lake, mountain, natural park, and so on), considering also availability of good, close-by hotels …” Answering Search Queries with CrowdSearcher
  6. 6. Background: semantic multi-domain search “… expand the search to get information about available restaurants near the candidate concert locations, news associated to the event and possible options to combine further events …” Answering Search Queries with CrowdSearcher
  7. 7. Liquid Query:Query Submission [WWW2010] Example Scenario 1: Trip planner for events Concert Hotels query conditions query conditions Answering Search Queries with CrowdSearcher
  8. 8. Liquid Query:Query Execution Answering Search Queries with CrowdSearcher
  9. 9. Liquid Query: alternative visualizationsand domain-independent platformExample Scenario 2: Scientific Publication search Answering Search Queries with CrowdSearcher
  10. 10. Problem Statement• When dealing with real-life problems, people do not trust the web completely • Want to go back to discussion with people • Expect insights, opinions, reassurance Answering Search Queries with CrowdSearcher
  11. 11. Problem Statement• When dealing with real-life problems, people do not trust the web completely • Want to go back to discussion with people • Expect insights, opinions, reassurance Answering Search Queries with CrowdSearcher
  12. 12. Problem Statement• When dealing with real-life problems, people do not trust the web completely • Want to go back to discussion with people • Expect insights, opinions, reassurance• Our proposal Interleaving and integration of exploratory search and social community input Answering Search Queries with CrowdSearcher
  13. 13. Social Search: increasing quality in search• From exploratory search to friends and experts feedback Initial query Exploration Exploratory step Human Search Search System System Exploration step System API Social API Database / Crowd / IR index Community Answering Search Queries with CrowdSearcher
  14. 14. From crowds to communities –The problems• Crowds vs. social networks • Friends or workforce?• Complex interleaving of factors. Including: • Intensity of social activity of the asker • Motivation of the responders • Topic • Information diffusion • Timing of the post (hour of the day, day of the week) • Context and language barrier Answering Search Queries with CrowdSearcher
  15. 15. Task management problemsTypical crowdsourcing problems:• Task splitting: the input data collection is too complex relative to the cognitive capabilities of users.• Task structuring: the query is too complex or too critical to be executed in one shot.• Task routing: a query can be distributed according to the values of some attribute of the collection.Plus:• Platform/community assignment: a task can be assigned to different communities or social platforms based on its focus Answering Search Queries with CrowdSearcher
  16. 16. Social Search – query properties• Invited community• Engagement platform• Execution platform• Query type: Like, Add, Sort / Rank, Comment, Modify• Visibility: public or private• Diffusion: enabled or not• Timespan Answering Search Queries with CrowdSearcher
  17. 17. Deployment: search on the social network• Multi-platform deployment Generated query template Embedded External Native Standalone application application application API Social/ Crowd platform Native Embedding behaviours Community / Crowd Answering Search Queries with CrowdSearcher
  18. 18. Deployment: search on the social network• Multi-platform deployment Answering Search Queries with CrowdSearcher
  19. 19. Deployment: search on the social network• Multi-platform deployment Answering Search Queries with CrowdSearcher
  20. 20. Deployment: search on the social network• Multi-platform deployment Answering Search Queries with CrowdSearcher
  21. 21. Deployment: search on the social network• Multi-platform deployment Answering Search Queries with CrowdSearcher
  22. 22. Example: Find your next job (exploration) Answering Search Queries with CrowdSearcher
  23. 23. Example: Find your job (social invitation) Answering Search Queries with CrowdSearcher
  24. 24. Example: Find your job (social invitation) Selected data items can be transferredto the crowd question Answering Search Queries with CrowdSearcher
  25. 25. Find your job (response submission) Answering Search Queries with CrowdSearcher
  26. 26. Experimental setting• Some 150 users• Two classes of experiments: • Random questions on fixed topics: interests (e.g. restaurants in the vicinity of Politecnico), to famous 2011 songs, or to top-quality EU soccer teams • Questions independently submitted by the users• Different invitation strategies: • Random invitation • Explicit selection of responders by the asker• Outcome • 175 like and insert queries • 1536 invitations to friends • 95 questions (~55%) got at least one answer • 230 collected answers Answering Search Queries with CrowdSearcher
  27. 27. Experiments: Manual and random questions Answering Search Queries with CrowdSearcher
  28. 28. Experiments: Interest and relationship• Manually written and assigned questions are consistently more responded in time Answering Search Queries with CrowdSearcher
  29. 29. Experiments: Query type• Engagement depends on the difficulty of the task• Like vs. Add tasks: Answering Search Queries with CrowdSearcher
  30. 30. Experiments: Distribution of answers/invitation• Sometimes: more answers than invitations (limited cases) Answering Search Queries with CrowdSearcher
  31. 31. Experiment: Social platform• The question enactment platform role• Facebook vs. Doodle Answering Search Queries with CrowdSearcher
  32. 32. Experiment: Social platform• The question enactment platform role• Facebook vs. Doodle Answering Search Queries with CrowdSearcher
  33. 33. Experiment: Posting time• The question enactment platform role• Facebook vs. Doodle Answering Search Queries with CrowdSearcher
  34. 34. Conclusions and future workStatus• the chances to get responses depend a lot on the consistency of the users’ community and on the mechanisms that are exploited for inviting the users and for collecting the responsesFuture work• More experiments (e.g., vs. sociality of users, vs. crowds, …)• Not only search: active integration of web structured data and social sensorsSome ads• Search Computing book series (Springer LNCS)• Workshop Very Large Data Search at VLDB• VLDB Journal special issue (deadline Sept 2012) Answering Search Queries with CrowdSearcher
  35. 35. www.search-computing.org @searchcomputingThanks!Questions? @marcobrambi marco.brambilla@polimi.it

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