This is a brief introduction to the FindiLike system.

1. FindiLike Hotel Search
www.findilike.com

2. What is FindiLike Hotel Search?
 A novel search engine: Finds & ranks entities by user
preferences
 Structured preferences
 Unstructured opinion preferences
E.g. Hotel search
 Structured: price [$0-$100], distance [5 miles from campus]
 Unstructured: “friendly service”, “clean”, “good views”
 Beyond search: Support for analysis of entities
 Opinion summaries
 Tag cloud visualization
 Browse review space

3. FindiLike Hotel search vs. Product Search?
Query
Topic keywords
“dell laptop”
Set of preferences
price, distance, opinions…
Ranking Keyword match
Mixed ranking strategy
Based on preferences
Analysis Limited/No tools
Opinion analysis tools
Tag cloud, summaries
Filters
Filter by common
attributes
Preferences act as
filters
findilikeProduct Search

4. How does FindiLike rank entities?
“clean”, “safe” $30-$60, Within 5 miles of..
Structured prefsOpinion prefs
Query
Review Browsing
Review Tag Clouds
Opinion Summaries
Results
Opinion Tools
Combined
Entity Scoring
Results
Summarization
Query
Parsing
Opinon
Expansion
Entity
Scoring
Entity
Scoring
Opinion Repository Structured Data
Query
Parsing
Ranking Engine
Opinion Matching Structured Matching

5. FindiLike Hotel Search Features
 Search for hotels based on Opinions, Distance, Price
 Analyze hotels
 Review summaries
 Tag cloud visualization of reviews
 Browse review space
 Book hotels from known providers
 Hotels.com
 Hotelscombined.com
 Access to more information about hotels
 Hotels.com
 Google Places

6. Finding “clean” hotels in Los Angeles close to
“Universal Studios”

7. price prefopinion prefs
location desired opinions
distance pref
results
Finding “clean” hotels in Los Angeles close to
“Universal Studios” - Interface

8. selected distance “5 miles from universal…”
preferred opinion “clean hotel”
preferred city “los angeles”
matching hotels
Finding “clean” hotels in Los Angeles close to
“Universal Studios” - Interface

9. Finding “clean” hotels in Los Angeles close to
“Universal Studios” - Results (List View)

10. Finding “clean” hotels in Los Angeles close to
“Universal Studios” - Results (Map View)

11. Finding “clean” hotels in Los Angeles close to
“Universal Studios” - Results (List View)
Results are ranked based on how well the
preferences are matched

12. Finding “clean” hotels in Los Angeles close to
“Universal Studios” - Results (List View)
YourMatch: Score of how well
preferences are matched [1-5]
2nd Best Match
Best Match

13. Finding “clean” hotels in Los Angeles close to
“Universal Studios” - Results (List View)
Fine Grained Match Info
Summary
Summary

14. Finding “clean” hotels in Los Angeles close to
“Universal Studios” - Results (List View)
Scoring: How well this hotel ranks in
relation to other hotels in Los Angeles
with respect to “clean hotel”
Scoring: Is this hotel within the
selected distance limit?

15. Finding “clean” hotels in Los Angeles close to
“Universal Studios” - Results (List View)
Rank 1
Opinion score: 4
Distance score: 5
Rank 2
Opinion score: 4
Distance score: 4 (exceeds
selected distance by 1 mile)

16. Finding “clean” hotels in Los Angeles close to
“Universal Studios” - Analysis Tools
What’s Buzzing:
Tag cloud of reviews
People Think:
Opinion Summaries
Click on selected opinions:
Browse review space

17. Finding “clean” hotels in Los Angeles close to
“Universal Studios” - Analysis Tools
Tag clouds
weighted by frequency
Related snippets
(“convenient location”)

18. Finding “clean” hotels in Los Angeles close to
“Universal Studios” - Analysis Tools
Opinion summaries
readable, well-formed
Related snippets

19. Finding “clean” hotels in Los Angeles close to
“Universal Studios” - Analysis Tools
Browse reviews related to
“parking”

20. Thank you!
Contact:
Kavita Ganesan
Email: kganes@findilike.com
Personal web: kavita-ganesan.com
Partnership requests/licensing: info@findilike.com
www.findilike.com
Relevant Publications:
 Ganesan, Kavita A., and Zhai ChengXiang , Opinion-Based Entity Ranking, Information
Retrieval, Volume 15, Issue 2, (2012)
 Ganesan, Kavita A., Zhai ChengXiang, and Han Jiawei , Opinosis: A Graph Based Approach to
Abstractive Summarization of Highly Redundant Opinions , Proceedings of the 23rd
International Conference on Computational Linguistics (COLING '10), (2010)
 Ganesan, Kavita A., Zhai ChengXiang, and Viegas Evelyne , Micropinion Generation: An
Unsupervised Approach to Generating Ultra-Concise Summaries of Opinions, Proceedings
of the 21st International Conference on World Wide Web 2012 (WWW '12), (2012)