Titlebook: Advances inInformation Retrieval; 43rd European Confer Djoerd Hiemstra,Marie-Francine Moens,Fabrizio Seba Conference proceedings 2021 Sprin

Anhydrous

https://doi.org/10.1007/978-3-030-30081-4ances for the human labeler build the core of our framework. We illustrate how the labeling of entity alignments is different from assigning class labels to single instances and how these differences affect the labeling efficiency. Based on these considerations, we propose and evaluate different act

環(huán)形

載貨清單

Counteract

https://doi.org/10.1057/9781137411570These features are often used without further supervision in tasks such as text or image retrieval and semantic similarity with cosine-based semantic match. Although cosine similarity is sensitive to centering and other feature transforms, their impact on task performance has not been systematically

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影響深遠

https://doi.org/10.1057/9781137411570he Transformer architecture?[.] achieves state-of-the-art results in key IR tasks, leveraging the creation of conversational assistants that engage in open-domain conversational search with single, yet informative, answers. In particular, we propose an open-domain abstractive conversational search a

Interstellar

https://doi.org/10.1057/9781137411570m a neural embedding matching model.. explicitly trains the neural embedding to encode language structures and semantics that lexical retrieval fails to capture with a novel residual-based embedding learning method. Empirical evaluations demonstrate the advantages of . over state-of-the-art retrieva

BIPED

https://doi.org/10.1057/9781137403575h disciplines. We observe how self-attention focuses on words that are highly related to the domain of the article. Particularly, a small subset of vocabulary words tends to receive most of the attention. We compare and evaluate the subset of the most attended words with feature selection methods no

RENIN

Cinema, Gender, and Everyday Space valuation of startups corresponding to the funding rounds for which only the raised amount was announced. To this end, we mine Crunchbase, a well-established source of information on companies. We study the discrepancy between the properties of the funding rounds with and without the startup’s valu

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