This document discusses expertise search and proposes a bibliographical-based faceted search framework. It describes the problem with current faceted search approaches that use general predefined facets rather than facets extracted from bibliographical texts. The proposed framework first extracts facet values from texts using natural language processing techniques. It then generates facet-value pairs to refine search results. The framework was evaluated on a dataset of bibliographical records using precision and recall measured against human experts. The framework aims to improve discovery of expertise by allowing refinement of search results based on extracted facets from bibliographical texts.

1. Bibliographical-
based Facets
for Expertise
Search
Gan Keng Hoon
School of Computer Sciences
USM

2. Contents ofThis Presentation
Expertise Search
Problem
Bibliographical-based Facets
Framework Overview

3. Expertise Search
Expertise search is a process of finding
information related to experts in their
areas of expertise.
Organization like universities, research
centers, companies.

4. Expertise Search
Medical Setting: Looking for expertise of all doctors in a
country.
Research Setting: Looking for researcher to review a paper.
Academic Setting: Looking for supervisor related to my
research interest.

5. Expertise Search: Scope ofThis Study
We know there are many interesting expertise out there ..
However, we need to choose one most familiar domain
Bibliographical Domain
&
Researchers/Authors/Academics

6. Expertise Search
The search of experts is normally linked to specific
intentions, such as, looking for someone who published at
particular venues, someone knows a mathematical model,
algorithms and so forth.

7. Expertise Search: Motivation
Improve the discovery of expertise
Who is familiar with bee
colony algo ?
Who hasTREC data set?
Who is in the area of
security?
Source: Part of Academic Staff from
School of Computer Sciences Site

8. Expertise Search: Motivation
Apart from solving this using Question Answering approach,
Faceted Search

9. Expertise Search: Motivation
Faceted Search
allowing users to explore a collection of information
by applying multiple filters.
Year
Venue
Type
Coauthor
…

10. Problem
The current facets are general filter
A facet and its value is normally given.
E.g.
“Year” facet and its value
“2014”

11. Problem
Cannot be used to answer the questions raised.
Who knows generative
model?

12. Problem
Facets like algorithm, framework, model, application etc. are may be
useful to refine the search results.
Challenge to extract the value dynamically
FacetValue

13. Problem
Refine by Framework
Bee Colony Optimization
…
Refine by Algorithm
….
Refine by Data Set
….

14. Problem
Challenging
as these values are normally not specified as part of the
structured/descriptive information of a bibliographical text.
<year>2015</year>
Scattered throughout the text, e.gTitle, Abstract, Headings,
Paragraphs !

15. Framework Overview

16. Framework Overview
FacetValue Extraction
i. Tokenization of sentence using connective words.
ii. Detection of Facet
iii. N-gram to find the common phrase nearby Facet.
Example,
Solving AsymmetricTraveling Salesman Problems using a generic Bee
Colony Optimization framework with insertion local search

17. Framework Overview
FacetValue Generation
i. Search Query
ii. Retrieval of Search Results
iii. Generate facet-value based on subset of results.

18. Framework Overview
Refine by Framework
Bee Colony Optimization
…
Refine by Algorithm
Modified Intelligent
Water Drops
IWD
….
Refine by Data Set
Malay broadcast news
….

19. Evaluation Plan
Dataset
DBLP Bibliographical records of School of Computer Sciences
Benchmarking
Human expert, the expert themselves to judge.
Accuracy
Precision and Recall Measure

20. Application Bibliographical
Facets

21. THANKYOU
Contact
khgan@usm.my
ir.cs.usm.my