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.

A Tree Sequence Alignment-based Tree-to-Tree Translation Model

Abstract: This paper presents a translation model that is based on tree sequence alignment, where a tree sequence refers to a single sequence of subtrees that covers a phrase. The model leverages on the strengths of both phrase-based and linguistically syntax-based method. It automatically learns aligned tree sequence pairs with mapping probabilities from word-aligned biparsed parallel texts. Compared with previous models, it not only captures non-syntactic phrases and discontinuous phrases with linguistically structured features, but also supports multi-level structure reordering of tree typology with larger span. This gives our model stronger expressive power than other reported models. Experimental results on the NIST MT-2005 Chinese-English translation task show that our method statistically significantly outperforms the baseline systems.

Term suggestion for multi-sense query

Abstract: Systems and methods for related term suggestion are described. In one aspect, term clusters are generated as a function of calculated similarity of term vectors. Each term vector having been generated from search results associated with a set of high frequency of occurrence (FOO) historical queries previously submitted to a search engine. Responsive to receiving a term/phrase from an entity, the term/phrase is evaluated in view of terms/phrases in the term clusters to identify one or more related term suggestions.

Compound or phrase? English noun-plus-noun constructions and the stress criterion

Abstract: This article argues that English noun-plus-noun constructions (‘NNs’) originate both in the lexicon and in the syntax. It distinguishes between complement–head and attribute–head NNs, as well as between fore-stressed and end-stressed NNs. It argues that complement-head NNs are fore-stressed and originate in the lexicon while attribute–head NNs typically have end-stress and syntactic provenance. The latter are, however, potentially subject to diachronic lexicalization, which may moreover involve the adoption of fore-stress. Hence, lexical NNs may be fore-stressed or end-stressed while phrasal NNs must be end-stressed. Although further potential sources of irregularity are identified, it is demonstrated that the model's predictive power is fairly robust and that, where it fails to predict firm stress patterns, it predicts their variability.

Selection of search phrases to suggest to users in view of actions performed by prior users

Abstract: A search engine system uses information about historical query submissions to a search engine to suggest previously-submitted, related search phrases to users. The related search phrases are preferably suggested based on a most recent set of query submission data (e.g., the last two weeks of submissions), and thus strongly reflect the current searching patterns or interests of users. In one embodiment, the related search phrases are scored and selected for display based at least in-part on (a) a frequency with which each search phrase has been submitted, and/or (b) an evaluation of the “usefulness” of each search phrase, as reflected by actions performed by prior users while viewing corresponding search results.