Titlebook: Masters Theses in the Pure and Applied Sciences; Accepted by Colleges Wade H. Shafer Book 1997 Plenum Press, New York 1997 agricultural eco

冒烟

Wade H. ShaferLP techniques to improve the quality of the produced summaries. The study reported in this paper seeks to establish whether Anaphora Resolution (AR) can improve the quality of generated summaries, and to assess whether AR has the same impact on text from different subject domains. Summarisation eval

大洪水

Wade H. Shafericularly to Question Answering (QA). Indeed, Passage Retrieval (PR) is a longstanding problem in QA, that has been widely studied over the last decades and still requires further efforts in order to enable a user to have a better chance to find a relevant answer to his human natural language questio

Enzyme

Wade H. Shafergoal of our work is to semantically enrich raw data by linking the mentions of named entities in the text to the corresponding known entities in knowledge bases. In our approach multiple aspects are considered: the prior knowledge of an entity in Wikipedia (i.e. the keyphraseness and commonness feat

inquisitive

Book 1997ysis and Synthesis (CINDAS)* at Purdue University in 1957, starting its coverage of theses with the academic year 1955. Beginning with Volume 13, the printing and dis­ semination phases of the activity were transferred to University Microfilms/Xerox of Ann Arbor, Michigan, with the thought that such

生气地

Data Analysis and Synthesis (CINDAS)* at Purdue University in 1957, starting its coverage of theses with the academic year 1955. Beginning with Volume 13, the printing and dis­ semination phases of the activity were transferred to University Microfilms/Xerox of Ann Arbor, Michigan, with the thought

foliage

ures and semantic matching of question topics with double attention. We evaluate the performance of our method on the well-known question answering site Stack exchange. The experiments show that our framework outperforms other state-of-the-art solutions to the problem.

BAN

ures and semantic matching of question topics with double attention. We evaluate the performance of our method on the well-known question answering site Stack exchange. The experiments show that our framework outperforms other state-of-the-art solutions to the problem.

defendant

Wade H. Shafere invariant and discriminative latent features across domains. Experimental results on the standard BioScope corpus show the superiority of the proposed neural architecture, which significantly outperforms the state-of-the-art on scope resolution in both in-domain and cross-domain scenarios.

Affable

Wade H. Shaferdecoder for one task is directly fed into the second-pass decoder for the other task, which can take full advantage of the explicit intent and slot information to achieve bidirectional guidance between the two tasks. Experiments on the ATIS and SNIPS datasets demonstrate the effectiveness and superi

摇摆