Results 31 to 40 of about 9,897,879 (386)

ID2SBVR: A Method for Extracting Business Vocabulary and Rules from an Informal Document

Big Data and Cognitive Computing, 2022
Semantics of Business Vocabulary and Rules (SBVR) is a standard that is applied in describing business knowledge in the form of controlled natural language.
Irene Tangkawarow, Riyanarto Sarno, Daniel Siahaan   +2 more
doaj   +1 more source

WANLI: Worker and AI Collaboration for Natural Language Inference Dataset Creation [PDF]

Conference on Empirical Methods in Natural Language Processing, 2022
A recurring challenge of crowdsourcing NLP datasets at scale is that human writers often rely on repetitive patterns when crafting examples, leading to a lack of linguistic diversity. We introduce a novel approach for dataset creation based on worker and
Alisa Liu, Swabha Swayamdipta, Noah A. Smith, Yejin Choi   +3 more
semanticscholar   +1 more source

Natural language processing [PDF]

, 2003
Beginning with the basic issues of NLP, this chapter aims to chart the major research activities in this area since the last ARIST Chapter in 1996 (Haas, 1996), including: (i) natural language text processing systems - text summarization, information ...
Adams, Amsler, Bangalore, Barker, Benoît, Bian, Bondale, Carrick, Ceric, Chandrasekar, Chang, Charniak, Chen, Chowdhury, Chowdhury, Costantino, Cowie, Craven, Craven, Craven, Dogru, Evans, Feldman, Fernandez, Gaizauskas, Glasgow, Haas, Hayes, Hayes, Hedlund, Herath, Ide, Isahara, Jelinek, Jeong, Jurafsky, Kazakov, Kehler, Khoo, Kim, King, Lange, Lee, Lehmam, Lehtokangas, Lewis, Liddy, Liddy, Lovis, Ma, Magnini, Mani, Manning, Marquez, Martinez, Martinez, McMurchie, Meyer, Mihalcea, Mock, Moens, Morin, Narita, Nerbonne, Oard, Ogura, Oudet, Owei, Paris, Pasero, Pedersen, Perez-Carballo, Petreley, Pirkola, Poesio, Rosenfield, Roux, Say, Scarlett, Schenker, Silber, Smeaton, Smeaton, Smith, Sokol, Song, Sparck Jones, Staab, Stock, Tolle, Trybula, Tsuda, Vickery, Waldrop, Warner, Weigard, Wilks, Wong, Yang, Yang, Zadrozny, Zweigenbaum   +101 more
core   +1 more source

Chat2VIS: Generating Data Visualizations via Natural Language Using ChatGPT, Codex and GPT-3 Large Language Models [PDF]

IEEE Access, 2023
The field of data visualisation has long aimed to devise solutions for generating visualisations directly from natural language text. Research in Natural Language Interfaces (NLIs) has contributed towards the development of such techniques.
Paula Maddigan, Teo Sušnjak
semanticscholar   +1 more source

Development of a software and hardware solution to identify trends in demand for goods

Вестник Дагестанского государственного технического университета: Технические науки, 2023
Objective. The aim of the research work is to develop a software solution for identifying trends in demand for consumer goods by analyzing big data.Method.
A. I. Miftahova, E. I. Yangirov, E. I. Karaseva, A. I. Yangirov, E. Yu. Nikulina, I. G. Drovnikova   +5 more
doaj   +1 more source

Readers and Reading in the First World War [PDF]

, 2015
This essay consists of three individually authored and interlinked sections. In ‘A Digital Humanities Approach’, Francesca Benatti looks at datasets and databases (including the UK Reading Experience Database) and shows how a systematic, macro-analytical
Edmund G. C. King, , Francesca Benatti, , Shafquat Towheed, , The Stanford Natural Language Processing Group, University of Sheffield   +4 more
core   +1 more source

Supervised Learning of Universal Sentence Representations from Natural Language Inference Data [PDF]

Conference on Empirical Methods in Natural Language Processing, 2017
Many modern NLP systems rely on word embeddings, previously trained in an unsupervised manner on large corpora, as base features. Efforts to obtain embeddings for larger chunks of text, such as sentences, have however not been so successful.
Alexis Conneau, Douwe Kiela, Holger Schwenk, Loïc Barrault, Antoine Bordes   +4 more
semanticscholar   +1 more source

Translating Natural Language to Planning Goals with Large-Language Models [PDF]

arXiv.org, 2023
Recent large language models (LLMs) have demonstrated remarkable performance on a variety of natural language processing (NLP) tasks, leading to intense excitement about their applicability across various domains.
Yaqi Xie, Chenyao Yu, Tongyao Zhu, Jinbin Bai, Ze Gong, Harold Soh   +5 more
semanticscholar   +1 more source

Performance Study of N-grams in the Analysis of Sentiments

Journal of Nigerian Society of Physical Sciences, 2021
In this work, a study investigation was carried out using n-grams to classify sentiments with different machine learning and deep learning methods. We used this approach, which combines existing techniques, with the problem of predicting sequence tags to
O. E. Ojo, A. Gelbukh, H. Calvo, O. O. Adebanji   +3 more
doaj   +1 more source

PyThaiNLP: Thai Natural Language Processing in Python [PDF]

NLPOSS, 2023
We present PyThaiNLP, a free and open-source natural language processing (NLP) library for Thai language implemented in Python. It provides a wide range of software, models, and datasets for Thai language.
Wannaphong Phatthiyaphaibun, Korakot Chaovavanich, Charin Polpanumas, Arthit Suriyawongkul, Lalita Lowphansirikul, Pattarawat Chormai, Peerat Limkonchotiwat, Thanathip Suntorntip, Can Udomcharoenchaikit   +8 more
semanticscholar   +1 more source