JCDL/ICADL 2010 Report

Kazunari Sugiyama9th July, 2010

Outline of JCDL/ICADL 2010

• Venue– Gold Coast, Queensland, Australia

Outline of JCDL/ICADL 2010

• Acceptance ratio– Full paper: 29.1% (32/110)– Short paper: 28.9% (13/45)

• Attendees– 206 people

• Next JCDL and ICADL– JCDL: Ottawa, Canada, June 2011– ICADL: Beijing, China, Oct 2011

Paper Introduction

“Context Identification of Sentences in Related Work Sections using a Conditional Random Field: Towards Intelligent Digital Libraries”

M. A. Angrosh, S. Cranefield, N. Stanger (University of Otago, New Zealand)

Aim

• Context identification and sentence classification with Conditional Random Field (CRF)

• Target sentences– Sentences in related work sections

• Features– Citation features– Sentence features

Rhetorical Pattern in Related Work Section

Their defined classes• Background

– Background (BG)

• Citation sentences– Related work description – Citation sentence (RWD_CS)– Related work outcome – Citation sentence (RWO_CS)– Related work strength – Citation sentence (RWS_CS)

• Description sentences– Related work description (RWD)– Related work outcome (RWO)– Related work strength (RWS)

• Research gap sentences– Related work shortcoming (RWSC)– Contrasting work for other work (CWOW)

• Alternate approaches– Alternate work for a related work – Citation sentence (AWRW_CS)– Alternate approach to a related work (AARW)

• Current work– Current work outcome (CWO)– Current work shortcoming (CWSC)

Features• Citation features– The presence of citation in sentences

• Sentence features– The presence of certain terms• Background terms

– “This section presents an overview of …”‘overview,’ ‘most research,’ ‘many researchers,’ …

• Strength terms– Mainly describe the strength of cited works

‘improve,’ ‘better,’ ‘performance,’ ‘aids,’ …

Experiments

• Dataset– 50 research articles randomly selected from the

Lecture Notes in Computer Science (LNCS)• 1063 sentences in total

• Evaluation measures– Precision– Recall– F

Experimental Results

Summary of this paper

• Proposed an approach classification of sentences in related work sections

• Use CRF to achieve this goal• Effective in using both citation and sentence

features