Zobrazeno 1 - 10
of 111
pro vyhledávání: '"Andrew Trotman"'
Publikováno v:
Frontiers in Genetics, Vol 13 (2022)
We present a novel approach to the Metagenomic Geolocation Challenge based on random projection of the sample reads from each location. This approach explores the direct use of k-mer composition to characterise samples so that we can avoid the comput
Externí odkaz:
https://doaj.org/article/5677cb1f1c414fee8e1a074a086e13ab
Efficient Document-at-a-Time and Score-at-a-Time Query Evaluation for Learned Sparse Representations
Publikováno v:
ACM Transactions on Information Systems.
Researchers have had much recent success with ranking models based on so-called learned sparse representations generated by transformers. One crucial advantage of this approach is that such models can exploit inverted indexes for top- k retrieval, th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9b2e462ae339f7d021d5f54a35319a0b
https://doi.org/10.1145/3576922
https://doi.org/10.1145/3576922
Publikováno v:
Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4cfb0c95717d6ab03edb07ee16c91f16
https://doi.org/10.1145/3477495.3531657
https://doi.org/10.1145/3477495.3531657
Autor:
Andrew Trotman, Vaughan Kitchen
Publikováno v:
Information Processing & Management. 59:103102
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::af5feaaf99d1bbaa55f43f0983f411ea
https://doi.org/10.1016/j.ipm.2022.103102
https://doi.org/10.1016/j.ipm.2022.103102
Autor:
Matt Crane, Andrew Trotman
Publikováno v:
Software: Practice and Experience. 49:942-950
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4ee975f77b905902fe3c2d5e233627b3
https://doi.org/10.1002/spe.2683
https://doi.org/10.1002/spe.2683
Autor:
Andrew Trotman, Kat Lilly
Publikováno v:
SIGIR
We present JASSjr, a minimalistic trec_eval compatible BM25-ranking search engine that can index small TREC data sets such as the Wall Street Journal collection. We do this for several reasons. First, to demonstrate how a term-at-a-time (TAAT) search
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::620d6e2761276999992e3f7472e9290d
https://doi.org/10.1145/3397271.3401413
https://doi.org/10.1145/3397271.3401413
Publikováno v:
ACM Transactions on Information Systems. 36:1-31
The effectiveness of a search engine is typically evaluated using hand-labeled datasets, where the labels indicate the relevance of documents to queries. Often the number of labels needed is too large to be created by the best annotators, and so less
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8a4e9a339642923cd5b43f337742a329
https://doi.org/10.1145/3186195
https://doi.org/10.1145/3186195
Autor:
Yiu-Chang Lin, Sindhuja Venkatesh, Maarten de Rijke, Xu Yinghui, Surya Kallumadi, Jon Degenhardt, Andrew Trotman, Luo Si
Publikováno v:
ACM SIGIR Forum. 51:128-138
The SIGIR 2017 Workshop on eCommerce (ECOM17), was a full day workshop that took place on Friday, August 11, 2017 in Tokyo, Japan. The purpose of the workshop was to serve as a platform for publication and discussion of Information Retrieval and NLP
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ad032292f158e91f4f27952b021896d6
https://doi.org/10.1145/3190580.3190600
https://doi.org/10.1145/3190580.3190600
Publikováno v:
Information Processing & Management. 58:102599
Sarcasm target detection (identifying the target of mockery in a sarcastic sentence) is an emerging field in computational linguistics. Although there has been some research in this field, accurately identifying the target still remains problematic e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e5599d2b87436833a1c11588949fab0f
https://doi.org/10.1016/j.ipm.2021.102599
https://doi.org/10.1016/j.ipm.2021.102599
Autor:
Andrew Trotman, Jimmy Lin
Publikováno v:
Information Retrieval Journal. 20:199-220
This paper explores the performance of top k document retrieval with score-at-a-time query evaluation on impact-ordered indexes in main memory. To better understand execution efficiency in the context of modern processor architectures, we examine the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b3db89f926491a97bf1a2b75f8655250
https://doi.org/10.1007/s10791-016-9291-5
https://doi.org/10.1007/s10791-016-9291-5