kiminh / product_attribute_summary

product automatic attributes discovery and summary

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Product Review Based Aspect Extraction

This repository contains some basic methods for Aspect Extraction, as denoted in Step 1 of this research statement.

Directory structure

.
├── README.md
├── config      # config files
├── data        # compressed and decompressed txt data
├── label       # manually attached labels to use as test set
├── output      # generated output with file extension `*.keywords`
└── src         # code

Papers

Phrase extraction

id paper code
autophrase Shang et al., Automated Phrase Mining from Massive Text Corpora, accepted by IEEE Transactions on Knowledge and Data Engineering, Feb. 2018 https://github.com/luozhouyang/AutoPhraseX
kea Witten et al., KEA: Practical Automatic Keyphrase Extraction, 2005. https://github.com/boudinfl/pke
kpminer El-Beltagy and Rafea, KP-Miner: Participation in SemEval-2, 2010. https://github.com/boudinfl/pke
multipart Boudin, Unsupervised Keyphrase Extraction with Multipartite Graphs, NAACL 2018. https://github.com/boudinfl/pke
positionrank Florescu and Caragea, PositionRank: An Unsupervised Approach to Keyphrase Extraction from Scholarly Documents, ACL 2017. https://github.com/boudinfl/pke
singlerank Wan and Xiao, CollabRank: Towards a Collaborative Approach to Single-Document Keyphrase Extraction, 2008. https://github.com/boudinfl/pke
textrank Mihalcea and Tarau, TextRank: Bringing Order into Texts, 2004. https://github.com/boudinfl/pke
tfidf - https://github.com/boudinfl/pke
topicalpagerank Sterckx et al., Topical Word Importance for Fast Keyphrase Extraction, 2015 https://github.com/boudinfl/pke
topicrank Bougouin et al., TopicRank: Graph-Based Topic Ranking for Keyphrase Extraction, 2013 https://github.com/boudinfl/pke
yake Campos et al., YAKE! Keyword extraction from single documents using multiple local features, 2020 https://github.com/boudinfl/pke

Aspect extraction

id paper code supervised result
mate Angelidis and Lapata, Summarizing Opinions: Aspect Extraction Meets Sentiment Prediction and They Are Both Weakly Supervised, https://github.com/stangelid/oposum semi- on keyboard dataset from electronic data mate.jsonl
acos Cai et al., Aspect-Category-Opinion-Sentiment Quadruple Extraction with Implicit Aspects and Opinions, ACL 2021 https://github.com/NUSTM/ACOS yes
cat Embarrassingly Simple Unsupervised Aspect Extraction, ACL 2020 https://github.com/clips/cat no
AspMem Chao Zhao and Snigdha Chaturvedi, Weakly-Supervised Opinion Summarization by Leveraging External Information, AAAI 2020 https://github.com/zhaochaocs/AspMem no on keyboard dataset from electronic data aspmem.json

Run

pip install -r requirements.txt
cd src
python main.py

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product automatic attributes discovery and summary


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