This collection consists of ~20M web queries collected from ~650k users over three months.
The data is sorted by anonymous user ID and sequentially arranged.
Here at Google Research we have been using word n-gram models for a variety of R&D projects, such as statistical machine translation, speech recognition, spelling correction, entity detection, information extraction, and others. While such models have usu
Expect to see an emphasis on the scholarly and research implications of the acquisition. I’m no Ph.D., but it boggles my mind to think what we might be able to learn about ourselves and the world around us from this wealth of data. And I’m certain we’ll learn things that none of us now can even possibly conceive.
S-Match is an open source Java framework for semantic matching. It contains semantic matching, minimal semantic matching and structure preserving semantic matching algorithm implementations.
Scientext is a new, on-line French and English corpus of scientific texts. The corpus includes 4.8 million running tokens in French, 13 million words of research articles in English (medicine and biology), and an English-language sub-corpus of French undergraduate students’ texts (1,1 million words). The corpus is organized to facilitate the linguistic study of authorial position and reasoning in scientific articles through phraseology and lexico-grammatical markers linked to causality.
T. McCoy, E. Pavlick, und T. Linzen. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, Seite 3428--3448. Florence, Italy, Association for Computational Linguistics, (Juli 2019)
S. Wunderlich, M. Ring, D. Landes, und A. Hotho. International Joint Conference: 12th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2019) and 10th International Conference on EUropean Transnational Education (ICEUTE 2019) - Seville, Spain, May 13-15, 2019, Proceedings, Volume 951 von Advances in Intelligent Systems and Computing, Seite 14--24. Springer, (2019)
K. Jiang, D. Wu, und H. Jiang. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), Seite 318--323. (2019)
N. Dehouche, und A. Wongkitrungrueng. Proceedings of ANZMAC 2018: The 20th Conference of the Australian and New Zealand Marketing Academy. Adelaide (Australia), Seite 3--5 December. (2018)
M. Braun, S. Krebs, F. Flohr, und D. Gavrila. (2018)cite arxiv:1805.07193Comment: Submitted to IEEE Trans. on Pattern Analysis and Machine Intelligence.
Z. Yang, P. Qi, S. Zhang, Y. Bengio, W. Cohen, R. Salakhutdinov, und C. Manning. Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Seite 2369--2380. Brussels, Belgium, Association for Computational Linguistics, (2018)
M. Braun, S. Krebs, F. Flohr, und D. Gavrila. (2018)cite arxiv:1805.07193Comment: Submitted to IEEE Trans. on Pattern Analysis and Machine Intelligence.