English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The work presented in this book is motivated by the goal of applying linguistic theorybuilding to the concrete needs of potential linguistic applications such as question answering, dialogue systems, andmachine translation. To pursue this goal, a translation of linguistic theory into a framework of “practical linguistics” is suggested. Database Semantics (DBS) is presented as a first step towards such a framework. It models the communication between cognitive agents, which can be used, for example, to implement the communicative abilities of a cognitive robot. DBS serves as a single underlying format for modeling communication in that it lends itself to an account of both language processing and language production (thinking is added as a separate component, which refers to inferencing on stored information, and activating content to be verbalized). As such an underlying format, it can be used to describe linguistic as well as extralinguistic content (to represent utterances and the context, respectively). Being explicitly designed for practical applications, DBS deliberately ignores linguistic phenomena considered irrelevant for these (e.g., quantifier scope). The structure of the book is as follows. It has threemain parts, which introduce DBS, outline the range of constructions covered by DBS so far, and specify fragments that can be processed or produced in the framework of DBS. There is also an appendix with two sections on the treatment of word-order variation in DBS and on the global architecture of DBS systems, and a glossary. The first part of the book starts with general principles of linguistic analysis that apply to DBS. These principles include incrementality (input is to be processed successively as it comes in, which yields an analysis for incomplete as well as complete chunks of input; the syntactic basis for this strategy is Left-Associative Grammar [Hausser 1992]), surface orientation (no empty categories), and a focus on communication (description formalisms must be able to handle turn-taking, i.e., language processing and production). After a sketch of the general theory of communication of which DBS is a part, DBS is presented in detail. It is implemented as a non-recursive data structure, that is, a list of feature structures called proplets (usually, one per word1) that are linked by coindexing the values of specific features.2 For example, subcategorizing elements (“functors”) have features whose values indicate their arguments and the other way around. In spite of its name, DBS does not offer a purely semantic representation of linguistic expressions. Although it does abstract away from purely syntactic phenomena such

computational linguistics - association for computational linguistics

<i>A Computational Model of Natural Language Communication</i> Roland Hausser (Friedrich-Alexander-Universität Erlangen-Nürnberg) Springer, 2006, xii+365 pp; hardbound, ISBN 3-540-35476-X/978-3-540-35476-5, €69.50

A Computational Model of Natural Language Communication Roland Hausser (Friedrich-Alexander-Universität Erlangen-Nürnberg) Springer, 2006, xii+365 pp; hardbound, ISBN 3-540-35476-X/978-3-540-35476-5, €69.50