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Workshop on Vector Space Modeling for Natural Language Processing 2015 — accepted papers

Workshop on Vector Space Modeling for Natural Language Processing 2015 is the 2015 edition of the Workshop on Vector Space Modeling for Natural Language Processing, held in Denver, Colorado, June 2015 (publisher: Association for Computational Linguistics). OpenAlex lists 27 papers of it; our library holds 3 with our summaries. Below: the most cited papers, every accepted paper, and ours with their topics, authors and institutions.

📍 Denver, Colorado · 🗓 June 2015

All accepted papers (27)

The most cited first; 3 with our summary link to their page here, the others to the original.

  1. A Vector Space Approach for Aspect Based Sentiment Analysis ↗Abdulaziz Alghunaim, Mitra Mohtarami, Scott Cyphers et al.
  2. Bilingual Word Representations with Monolingual Quality in MindThang Luong, Hieu Pham, Christopher D. Manningour summary
  3. Combining Distributed Vector Representations for Words ↗Justin Garten, Kenji Sagae, Volkan Ustun et al.
  4. Distributed Word Representations Improve NER for e-Commerce ↗Mahesh Joshi, Ethan Hart, Mirko Vogel et al.
  5. Named Entity Recognition for Arabic Social MediaAyah Zirikly, Mona Diabour summary
  6. Neural context embeddings for automatic discovery of word senses ↗Mikael Kågebäck, Fredrik Johansson, Richard Johansson et al.
  7. Short Text Clustering via Convolutional Neural Networks ↗Jiaming Xu, Peng Wang, Guanhua Tian et al.
  8. Simple Semi-Supervised POS Tagging ↗Karl Stratos, Michael Collins

See all 27 papers in Workshop on Vector Space Modeling for Natural Language Processing 2015 — accepted papers →

 Papers with our summary in our library (3)

The most cited first (OpenAlex citations plus our library's).

 Top topics

Topics of its works in our library, with the number of works on each.

Named entity recognition (1)Information extraction (1)Semitic languages (1)

 Fields

Arts and Humanities (3)Computer Science (3)

 Top authors

Authors with a page who published here most often: their works here, and the citations of those works.

 Top institutions

Institutions on the bylines of its works here, by the number of works.

Place and dates from the event's site or the ACL Anthology; works and citations from OpenAlex and our library.

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