@inproceedings{qasemizadeh-kallmeyer-2017-hhu,
    title = "{HHU} at {S}em{E}val-2017 Task 2: Fast Hash-Based Embeddings for Semantic Word Similarity Assessment",
    author = "QasemiZadeh, Behrang  and
      Kallmeyer, Laura",
    editor = "Bethard, Steven  and
      Carpuat, Marine  and
      Apidianaki, Marianna  and
      Mohammad, Saif M.  and
      Cer, Daniel  and
      Jurgens, David",
    booktitle = "Proceedings of the 11th International Workshop on Semantic Evaluation ({S}em{E}val-2017)",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/iwcs-25-ingestion/S17-2039/",
    doi = "10.18653/v1/S17-2039",
    pages = "250--255",
    abstract = "This paper describes the HHU system that participated in Task 2 of SemEval 2017, Multilingual and Cross-lingual Semantic Word Similarity. We introduce our unsupervised embedding learning technique and describe how it was employed and configured to address the problems of monolingual and multilingual word similarity measurement. This paper reports from empirical evaluations on the benchmark provided by the task{'}s organizers."
}