Liquid Query: Multi-domain Exploratory Search on the Web

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

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

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

An Example of multi-domain query
“… search for upcoming concertsclose to an attractive location (like a beach, lake, mountain, natural park, and so on), considering also availability of good, close-byhotels …”
Current approach the user can adopt:
Independently explore search services
Manually combine findings

An Example of multi-domain query
“… expand the search to get information about available restaurantsnear the candidate concert locations, news associated to the event and possible options to combine further events scheduled in the same days and located in a close-by place with respect to the first one…”

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)

Related work
Topic based search: instance of exploratory search centered on the goal of collecting information on a subject matter of interest from multiple sources
Kosmix: topic discovery engine, keyword search, a topic page summarizes the most relevant information on the subject
Hakia: resume pages for topics associated with user’s queries, natural language processing techniques

Related work
Structured Object Search:process queries and present results that address entities or real world objects described in Web pages
Google Squared: keyword search, results collected in a table (called a square) featuring all the attributes relevant to the result items as columns headers
Google Fusion Tables: upload data tables (e.g., spreadsheet files) and join (or “fuse”) the data in some column with other tables

The Liquid Query Approach
“ A new paradigm allowing users to formulate and get responses to multi-domain queries through an exploratory information seeking approach, based upon structured information sources exposed as software services…”
Compositeanswers obtained by aggregating search results from various domains
Highlightthe contribution of each search service
Joinof results based on the structural information afforded by the search service interfaces
Refinethe user query
Re-shape result list
http://www.search-computing.net/LQDemo/

Liquid Query Life Cycle

Liquid Query Template
service interfaces: high level representation of a data provisioning service which comprises input parameters, output parameters, and ranking attributes
connection patterns for joining the involved service interfaces
additional selection or join predicates
a default ranking function defined over the scores of service interfaces
sorting and clustering options that can be applied on the extracted result set
the size for the result pages
a set of available query expansions towards further domains
Example 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

Query Submission
Hotels
query conditions
Concert
query conditions

Query Execution

Result Exploration (SaaP - Search as a Process)
The current set of combinations is not satisfactory, so user asks for more values for a service (more one) or for all services (more all)
More concerts, more hotels, or more combinations
Add new information about further domains for selected combinations (expand)
Find close-by restaurants or co-located events
Aggregate information to ease analysis and readability (clustering, grouping)
Group events by venue
Reduce the number of shown items through filtering
Total walked distance for the night
Re-order (ranking or sorting)
Calculate derived values from existing ones
Total walked distance for the night
Alternative data visualization
Map, parallel coords, ...

The back-end: YQL - Yahoo Query Language
A language and a platform that let Web application query, filter, and combine data from different sources across the Internet through SQL-like statements
Remote Query Interaction PrimitivesYQL commands + locally computed join operation
Local Resultset Interaction and Local Manipulation Primitives client side (GoogleGears DB)
Data Visualization Primitives mashups with visualization libraries
SELECT title, city, Rating.AverageRating,
latitude, longitude
FROM Local.Search (0,100)
WHERE (latitude,longitude) IN
(SELECT latitude, longitude
FROM Upcoming.Events
WHERE category_id=“1” AND
min_date="2009-12-01" AND
max_date="2009-12-31" AND
location = "San Francisco" AND
search_text=”Jazz
)AND query=“Hotel” AND radius = “0.5”
AND Rating.AverageRating > 2
AND Rating.TotalRatings > 30
Flickr
Weather
Yahoo Upcoming
Yahoo Search
Amazon
Select / Create / Delete
NYTimes
Facebook
Music
Remote Filter, Sort, Limit
Local Filter, Sort, Limit

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

Overview of Search Computing and Liquid Query

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

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

Conclusions and future work
Liquid Query
exploits the power of underlying vertical search services by joining and matching results
grants multi-domain exploratory search through a combination of search interfaces and data visualization
Details: “Search Computing – Challenges and Directions”Ceri, Brambilla (eds.), book by Springer, April 2010
Future and ongoing works
thorough user evaluation studies
design of additional interaction and visualization options
implementation of visual tools for Liquid Query configuration
Integration of the Search Computing backend engine
Application of diversification and personalization to results

Thanks! Questions?
www.search-computing.it
bozzon@elet.polimi.it

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Liquid Query: Multi-domain Exploratory Search on the Web

by Alessandro Bozzon on Apr 29, 2010

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