SemEval-2010 Task 5 : Automatic Keyphrase Extraction from Scientific Articles
- Su Nam Kim, Olena Medelyan, Min-Yen Kan, Timothy Baldwin
- Computer ScienceInternational Workshop on Semantic Evaluation
- 15 July 2010
The participating systems were evaluated by matching their extracted keyphrases against manually assigned ones and the overall ranking of the submitted systems is presented.
Fast Matrix Factorization for Online Recommendation with Implicit Feedback
- Xiangnan He, Hanwang Zhang, Min-Yen Kan, Tat-Seng Chua
- Computer ScienceAnnual International ACM SIGIR Conference on…
- 7 July 2016
A new learning algorithm based on the element-wise Alternating Least Squares (eALS) technique is designed, for efficiently optimizing a Matrix Factorization (MF) model with variably-weighted missing data and exploiting this efficiency to then seamlessly devise an incremental update strategy that instantly refreshes a MF model given new feedback.
TriRank: Review-aware Explainable Recommendation by Modeling Aspects
- Xiangnan He, Tao Chen, Min-Yen Kan, Xiao Chen
- Computer ScienceInternational Conference on Information and…
- 17 October 2015
TriRank endows the recommender system with a higher degree of explainability and transparency by modeling aspects in reviews, and allows users to interact with the system through their aspect preferences, assisting users in making informed decisions.
Recognizing Implicit Discourse Relations in the Penn Discourse Treebank
- Ziheng Lin, Min-Yen Kan, H. Ng
- Computer ScienceConference on Empirical Methods in Natural…
- 6 August 2009
An implicit discourse relation classifier is presented in the Penn Discourse Treebank that considers the context of the two arguments, word pair information, as well as the arguments' internal constituent and dependency parses.
A PDTB-styled end-to-end discourse parser
- Ziheng Lin, H. Ng, Min-Yen Kan
- Computer ScienceNatural Language Engineering
- 3 November 2010
This work has designed and developed an end-to-end discourse parser- to-parse free texts in the PDTB style in a fully data-driven approach and significantly improves on the current state-of-the-art connective classifier.
Sequicity: Simplifying Task-oriented Dialogue Systems with Single Sequence-to-Sequence Architectures
- Wenqiang Lei, Xisen Jin, Min-Yen Kan, Z. Ren, Xiangnan He, Dawei Yin
- Computer ScienceAnnual Meeting of the Association for…
- 1 July 2018
A novel, holistic, extendable framework based on a single sequence-to-sequence (seq2seq) model which can be optimized with supervised or reinforcement learning is proposed which significantly outperforms state- of-the-art pipeline-based methods on large datasets and retains a satisfactory entity match rate on out-of-vocabulary (OOV) cases where pipeline-designed competitors totally fail.
ParsCit: an Open-source CRF Reference String Parsing Package
- Isaac G. Councill, C. Lee Giles, Min-Yen Kan
- Computer ScienceInternational Conference on Language Resources…
- 1 May 2008
Parsing package ParsCit is described, a freely available, open-source implementation of a reference string parsing package that wraps a trained conditional random field model with added functionality to identify reference strings from a plain text file, and to retrieve the citation contexts.
The ACL Anthology Reference Corpus: A Reference Dataset for Bibliographic Research in Computational Linguistics
- Steven Bird, R. Dale, Yee Fan Tan
- LinguisticsInternational Conference on Language Resources…
- 2008
This is a post-print of a paper from Sixth International Conference on Language Resources and Evaluation 2008, where six papers were presented, one of which was new to the literature.
Keyphrase Extraction in Scientific Publications
- T. Nguyen, Min-Yen Kan
- Computer ScienceInternational Conference on Asian Digital…
- 10 December 2007
In the evaluation using a corpus of 120 scientific publications multiply annotated for keyphrases, the system significantly outperformed Kea at the p < .05 level.
Fast webpage classification using URL features
- Min-Yen Kan, H. Thi
- Computer ScienceInternational Conference on Information and…
- 31 October 2005
This work demonstrates the usefulness of the uniform resource locator (URL) alone in performing web page classification and shows that in certain scenarios, URL-based methods approach the performance of current state-of-the-art full-text and link- based methods.
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