Results 1 to 10 of about 3,445,897 (351)

COVID-19 information retrieval with deep-learning based semantic search, question answering, and abstractive summarization. [PDF]

NPJ Digit Med, 2021
The COVID-19 global pandemic has resulted in international efforts to understand, track, and mitigate the disease, yielding a significant corpus of COVID-19 and SARS-CoV-2-related publications across scientific disciplines.
Esteva A, Kale A, Paulus R, Hashimoto K, Yin W, Radev D, Socher R.   +6 more
europepmc   +2 more sources

D2LLM: Decomposed and Distilled Large Language Models for Semantic Search [PDF]

Annual Meeting of the Association for Computational Linguistics
The key challenge in semantic search is to create models that are both accurate and efficient in pinpointing relevant sentences for queries. While BERT-style bi-encoders excel in efficiency with pre-computed embeddings, they often miss subtle nuances in ...
Zihan Liao, Hang Yu, Jianguo Li, Jun Wang, Wei Zhang   +4 more
openalex   +2 more sources

GenoSurf: metadata driven semantic search system for integrated genomic datasets. [PDF]

Database (Oxford), 2019
Many valuable resources developed by world-wide research institutions and consortia describe genomic datasets that are both open and available for secondary research, but their metadata search interfaces are heterogeneous, not interoperable and sometimes
Canakoglu A, Bernasconi A, Colombo A, Masseroli M, Ceri S.   +4 more
europepmc   +2 more sources

Semantic Product Search [PDF]

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019
We study the problem of semantic matching in product search, that is, given a customer query, retrieve all semantically related products from the catalog. Pure lexical matching via an inverted index falls short in this respect due to several factors: a) lack of understanding of hypernyms, synonyms, and antonyms, b) fragility to morphological variants ...
Priyanka Nigam, Yiwei Song, Vijai Mohan, Vihan Lakshman, Weitian (Allen) Ding, Ankit Shingavi, Choon Hui Teo, Hao Gu, Bing Yin   +8 more
semanticscholar   +5 more sources

Thalia: semantic search engine for biomedical abstracts. [PDF]

Bioinformatics, 2019
Summary Although the publication rate of the biomedical literature has been growing steadily during the last decades, the accessibility of pertinent research publications for biologist and medical practitioners remains a challenge. This article describes
Soto AJ, Przybyła P, Ananiadou S.
europepmc   +2 more sources

LitVar: a semantic search engine for linking genomic variant data in PubMed and PMC. [PDF]

Nucleic Acids Res, 2018
The identification and interpretation of genomic variants play a key role in the diagnosis of genetic diseases and related research. These tasks increasingly rely on accessing relevant manually curated information from domain databases (e.g. SwissProt or
Allot A, Peng Y, Wei CH, Lee K, Phan L, Lu Z.   +5 more
europepmc   +2 more sources

BioSearch: a semantic search engine for Bio2RDF. [PDF]

Database (Oxford), 2017
Biomedical data are growing at an incredible pace and require substantial expertise to organize data in a manner that makes them easily findable, accessible, interoperable and reusable.
Hu W, Qiu H, Huang J, Dumontier M.
europepmc   +2 more sources

SemEHR: A general-purpose semantic search system to surface semantic data from clinical notes for tailored care, trial recruitment, and clinical research. [PDF]

J Am Med Inform Assoc, 2018
Objective Unlocking the data contained within both structured and unstructured components of Electronic Health Records (EHRs) has the potential to provide a step change in data available forsecondary research use, generation of actionable medical ...
Wu H, Toti G, Morley KI, Ibrahim ZM, Folarin A, Jackson R, Kartoglu I, Agrawal A, Stringer C, Gale D, Gorrell G, Roberts A, Broadbent M, Stewart R, Dobson RJB.   +14 more
europepmc   +2 more sources

Large Language Models in Bio-Ontology Research: A Review. [PDF]

Bioengineering (Basel)
Biomedical ontologies are critical for structuring domain knowledge and enabling integrative analyses in the life sciences. Traditional ontology development is labor-intensive, requiring extensive expert curation.
Manda P.
europepmc   +2 more sources

Semantic Search Evaluation

arXiv.org
We propose a novel method for evaluating the performance of a content search system that measures the semantic match between a query and the results returned by the search system. We introduce a metric called "on-topic rate" to measure the percentage of results that are relevant to the query.
Zheng, Chujie, Wang, Jeffrey, Zhang, Shuqian Albee, Kishore, Anand, Singh, Siddharth   +4 more
openaire   +3 more sources