The document summarizes the Liquid Queries approach for multi-domain exploratory search across the web. Liquid Queries allows users to formulate queries across multiple semantic domains through an iterative process of querying services, exploring results, and refining queries. It aggregates results from different search services and domains, highlights the contribution of each, and allows joining results based on structural information. Key aspects include the Liquid Query template and life cycle, backend implementation using YQL, and demonstrations of the prototype. Future work aims to improve user evaluation, interactions, and personalization.

1. Liquid QueriesMulti-domain Exploratory Search on the Web Alessandro Bozzon, Marco Brambilla, Piero Fraternali, Stefano Ceri WWW 2010, Raleigh (NC) April, 29th 2010

2. Context The Web is a huge, heterogeneousdata source: Unstructured information Structured and semi-structured data Linked Data Documents are integrated with semi-structured or structured data and enriched with semantics Search as a service Google, Yahoo, Amazon, Twitter, YouTube, MySpace, and Facebook Viability of systems based upon search service orchestration

3. Problem Statement Web queries get increasingly complexand specialized as the searcher’s expertise grows Exploratory search Multi-step search processes From document searchto object/entity search Multi-domain queries multiple semantic fields of interest (e.g., travels, music, shows, food, movies, health, genetic diseases, etc.) domain-specific (aka, vertical) search engines provide more focused results than general-purpose ones the challenge is to match the results coming fromdifferentverticals

6. Related work Exploratory Search: user’s intent is primarily to learn more on a topic of interest Marchionini, G. Exploratory search: from finding to understanding. Communications ACM 49(4): 41-46 (2006) “… exploratory search, that blends querying and browsing strategies, from retrieval that is best served by analytical strategies…” Definition and analysis of the problem White, R. W., and Drucker, S. M. Investigating behavioral variability in web search. 16th WWW Conf. (Banff, Canada, 2007) Complex Search Vs. Exploratory Search Aula, A., and Russell, D.M. Complex and Exploratory Web Search. ISSS: Information Seeking Support Systems Workshop (Chapel Hill, NC, USA, June 2008)

10. Highlightthe contribution of each search service

11. Joinof results based on the structural information afforded by the search service interfaces

12. Refinethe user query

13. Re-shape result list http://www.search-computing.net/LQDemo/

14. Liquid Query Life Cycle

16. connection patterns for joining the involved service interfaces

17. additional selection or join predicates

18. a default ranking function defined over the scores of service interfaces

19. sorting and clustering options that can be applied on the extracted result set

20. the size for the result pages

21. a set of available query expansions towards further domainsExample scenario: Initial query on Concert and Hotel objects; possible expansions on Events, related News, Restaurants; distance ranking for Concert, Restaurant and Hotel; date ranking on News and Photos

22. Query Submission Hotels query conditions Concert query conditions

23. Query Execution

25. More concerts, more hotels, or more combinations

26. Add new information about further domains for selected combinations (expand)

27. Find close-by restaurants or co-located events

28. Aggregate information to ease analysis and readability (clustering, grouping)

29. Group events by venue

30. Reduce the number of shown items through filtering

31. Total walked distance for the night

32. Re-order (ranking or sorting)

33. Calculate derived values from existing ones

34. Total walked distance for the night

35. Alternative data visualization

37. Liquid Query Prototype Demo http://www.search-computing.net/LQDemo/

38. Overview of Search Computing and Liquid Query

39. Liquid Queries Prototype Architecture Query, Table and Action Configuration Local Data Configuration LQ Widget Configuration Query Configuration YQL Service Configuration

40. Liquid Query over Linked Data Demo Example Scenario: Scientific Publication search http://demo.search-computing.net/lq/v2/SeCoPaper/

42. grants multi-domain exploratory search through a combination of search interfaces and data visualization

44. design of additional interaction and visualization options

45. implementation of visual tools for Liquid Query configuration

46. Integration of the Search Computing backend engine