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researcher

Irwin King

The Chinese University of Hong Kong

84 papers hereh-index 7827.3k citations436 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author37
  • last author44

Across the 81 of 84 papers where every author was matched, so the position is known.

fields
  • cs.CL34
  • cs.LG19
  • cs.IR11
  • cs.CV9
  • cs.AI3
  • cs.SE3
affiliations
  • The Chinese University of Hong Kong
Homepage
same name
  • Irwin King — 23 papers, h 17
  • Irwin King — 22 papers, h 8
  • Irwin King — 15 papers, h 4
  • Irwin King — 13 papers, h 7
  • Irwin King — 12 papers, h 11
  • Irwin King — 9 papers

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20122023
most citedA Survey of Point-of-interest Recommendation in Location-based Social Networks

79 citations · 654 across the 53 of their papers we have counts for

collaborators
Showing 2018 · cs.CLShow all

4 papers · 2 filters

cs.CL2018

Topic Memory Networks for Short Text Classification

Jichuan Zeng, Jing Li, Yan Song +3

Many classification models work poorly on short texts due to data sparsity. To address this issue, we propose topic memory networks for short text classification with a novel topic…

cs.CL2018

Generating Distractors for Reading Comprehension Questions from Real Examinations

Yifan Gao, Lidong Bing, Piji Li +2

We investigate the task of distractor generation for multiple choice reading comprehension questions from examinations. In contrast to all previous works, we do not aim at preparin…

cs.CL2018

Title-Guided Encoding for Keyphrase Generation

Wang Chen, Yifan Gao, Jiani Zhang +2

Keyphrase generation (KG) aims to generate a set of keyphrases given a document, which is a fundamental task in natural language processing (NLP). Most previous methods solve this…

cs.CL2018

Difficulty Controllable Generation of Reading Comprehension Questions

Yifan Gao, Lidong Bing, Wang Chen +2

We investigate the difficulty levels of questions in reading comprehension datasets such as SQuAD, and propose a new question generation setting, named Difficulty-controllable Ques…

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