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Topic

Phrase

About: Phrase is a research topic. Over the lifetime, 12580 publications have been published within this topic receiving 317823 citations. The topic is also known as: syntagma & phrases.


Papers
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Journal ArticleDOI
TL;DR: In this article, a two-branch neural network is proposed to learn the similarity between image-sentence matching and visual grounding, which achieves high accuracies for phrase localization on the Flickr30K Entities dataset and for bi-directional imagesentence retrieval on Flickr30k and MSCOCO datasets.
Abstract: Image-language matching tasks have recently attracted a lot of attention in the computer vision field. These tasks include image-sentence matching, i.e., given an image query, retrieving relevant sentences and vice versa, and region-phrase matching or visual grounding, i.e., matching a phrase to relevant regions. This paper investigates two-branch neural networks for learning the similarity between these two data modalities. We propose two network structures that produce different output representations. The first one, referred to as an embedding network , learns an explicit shared latent embedding space with a maximum-margin ranking loss and novel neighborhood constraints. Compared to standard triplet sampling, we perform improved neighborhood sampling that takes neighborhood information into consideration while constructing mini-batches. The second network structure, referred to as a similarity network , fuses the two branches via element-wise product and is trained with regression loss to directly predict a similarity score. Extensive experiments show that our networks achieve high accuracies for phrase localization on the Flickr30K Entities dataset and for bi-directional image-sentence retrieval on Flickr30K and MSCOCO datasets.

391 citations

Journal ArticleDOI
TL;DR: A neurocognitive model of online comprehension that accounts for cross-linguistic unity and diversity in the processing of core constituents (verbs and arguments) and can derive the appearance of similar neurophysiological and neuroanatomical processing correlates in seemingly disparate structures in different languages.
Abstract: Real-time language comprehension is a principal cognitive ability and thereby relates to central properties of the human cognitive architecture. Yet how do the presumably universal cognitive and neural substrates of language processing relate to the astounding diversity of human languages (over 5,000)? The authors present a neurocognitive model of online comprehension, the extended argument dependency model (eADM), that accounts for cross-linguistic unity and diversity in the processing of core constituents (verbs and arguments). The eADM postulates that core constituent processing proceeds in three hierarchically organized phases: (1) constituent structure building without relational interpretation, (2) argument role assignment via a restricted set of cross-linguistically motivated information types (e.g., case, animacy), and (3) completion of argument interpretation using information from further domains (e.g., discourse context, plausibility). This basic architecture is assumed to be universal, with cross-linguistic variation deriving primarily from the information types applied in Phase 2 of comprehension. This conception can derive the appearance of similar neurophysiological and neuroanatomical processing correlates in seemingly disparate structures in different languages and, conversely, of cross-linguistic differences in the processing of similar sentence structures.

389 citations

Proceedings Article
04 Dec 2006
TL;DR: This work demonstrates that the trend toward predictability-sensitive syntactic reduction (Jaeger, 2006) is robust in the face of a wide variety of control variables, and presents evidence that speakers use both surface and structural cues for predictability estimation.
Abstract: If language users are rational, they might choose to structure their utterances so as to optimize communicative properties. In particular, information-theoretic and psycholinguistic considerations suggest that this may include maximizing the uniformity of information density in an utterance. We investigate this possibility in the context of syntactic reduction, where the speaker has the option of either marking a higher-order unit (a phrase) with an extra word, or leaving it unmarked. We demonstrate that speakers are more likely to reduce less information-dense phrases. In a second step, we combine a stochastic model of structured utterance production with a logistic-regression model of syntactic reduction to study which types of cues speakers employ when estimating the predictability of upcoming elements. We demonstrate that the trend toward predictability-sensitive syntactic reduction (Jaeger, 2006) is robust in the face of a wide variety of control variables, and present evidence that speakers use both surface and structural cues for predictability estimation.

387 citations

Patent
Roy Aaron Underwood1
30 Jul 1999
TL;DR: In this paper, a table of codes and associated text phrases is provided, and a plurality of services are executed, including retrieving a single one of the text phrases associated with each of the codes of the table is permitted.
Abstract: A system, method and article of manufacture are provided for maintaining application consistency. First, a table of codes and associated text phrases are provided. Such table of codes is stored on a local storage medium within an e-commerce computer architecture. Next, the table of codes is accessed on the local storage medium within the e-commerce computer architecture. One of the text phrases is subsequently retrieved by selecting a corresponding one of the codes of the table. During operation, modification of the text phrases associated with each of the codes of the table is permitted. A plurality of services are executed, including retrieving a single one of the text phrases, retrieving all of the text phrases in response to a single command, updating a single code and text phrase combination, updating all of the code and text phrase combinations, naming the table, adding a new code and text phrase combination, removing one of the code and text phrase combination, and adding another table.

375 citations

Proceedings ArticleDOI
06 Aug 2009
TL;DR: A novel approach for mining opinions from product reviews is presented, where it converts opinion mining task to identify product features, expressions of opinions and relations between them by taking advantage of the observation that a lot of product features are phrases.
Abstract: In this paper, we present a novel approach for mining opinions from product reviews, where it converts opinion mining task to identify product features, expressions of opinions and relations between them. By taking advantage of the observation that a lot of product features are phrases, a concept of phrase dependency parsing is introduced, which extends traditional dependency parsing to phrase level. This concept is then implemented for extracting relations between product features and expressions of opinions. Experimental evaluations show that the mining task can benefit from phrase dependency parsing.

372 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023467
20221,079
2021360
2020470
2019525
2018535