2017 QLUTatSemEval2017Task2WordSimil

(Meng et al., 2017) ⇒ Fanqing Meng, Wenpeng Lu, Yuteng Zhang, Ping Jian, Shumin Shi, and Heyan Huang. (2017). “QLUT at SemEval-2017 Task 2: Word Similarity Based on Word Embedding and Knowledge Base.” In: Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval@ACL 2017).

Subject Headings: Semantic Word Similarity; QLUT-SWS System; SemEval-2017 Task 2.

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Google Scholar: ~ 5 Citations

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Abstract

This paper shows the details of our system submissions in the task 2 of SemEval 2017. We take part in the subtask 1 of this task, which is an English monolingual subtask. This task is designed to evaluate the semantic word similarity of two linguistic items. The results of runs are assessed by standard Pearson and Spearman correlation, contrast with official gold standard set. The best performance of our runs is 0.781 (Final). The techniques of our runs mainly make use of the word embeddings and the knowledge-based method. The results demonstrate that the combined method is effective for the computation of word similarity, while the word embeddings and the knowledge-based technique, respectively, needs more deeply improvement in details.

1. Introduction

2. System Overview

In the subtask 1 (English monolingual word similarity) of this task, we have submitted two system runs, both of which are unsupervised. We mainly utilize the word embeddings method and the combined method.

The Figure 1 shows the framework of our system runs. In the top part of the figure, word1 and word2 are the input of our systems. Run1 utilizes the word embeddings method. Run2 utilizes the combined method, which is based on the word embeddings and knowledge-based method.

**Figure 1:** The framework of our system runs.

...

3. Evaluation

4. Conclusions and Future Work

Acknowledgments

Footnotes

References

BibTeX

@inproceedings{2017_QLUTatSemEval2017Task2WordSimil,
  author    = {Fanqing Meng and
               Wenpeng Lu and
               Yuteng Zhang and
               Ping Jian and
               Shumin Shi and
               Heyan Huang},
  editor    = {Steven Bethard and
               Marine Carpuat and
               Marianna Apidianaki and
               Saif M. Mohammad and
               Daniel M. Cer and
               David Jurgens},
  title     = {QLUT at SemEval-2017 Task 2: Word Similarity Based on Word Embedding
               and Knowledge Base},
  booktitle = {Proceedings of the 11th International Workshop on Semantic Evaluation
               (SemEval@ACL 2017)},
  pages     = {235--238},
  publisher = {Association for Computational Linguistics},
  year      = {2017},
  url       = {https://doi.org/10.18653/v1/S17-2036},
  doi       = {10.18653/v1/S17-2036},
}

	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2017 QLUTatSemEval2017Task2WordSimil	Fanqing Meng Wenpeng Lu Yuteng Zhang Ping Jian Shumin Shi Heyan Huang			QLUT at SemEval-2017 Task 2: Word Similarity Based on Word Embedding and Knowledge Base						2017