NATURAL LANGUAGE PROCESSING and Human–Computer Interaction

2013 ◽  
Vol 35 (5) ◽  
pp. 415-416
Author(s):  
Rafael Valencia-García ◽  
Francisco García-Sánchez
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Human Computer Interaction ◽  
Language Processing ◽  
Computer Interaction

Dagstuhl seminar 19461 on conversational search

2020 ◽  
Vol 54 (1) ◽  
pp. 1-11
Author(s):  
Avishek Anand ◽  
Lawrence Cavedon ◽  
Matthias Hagen ◽  
Hideo Joho ◽  
Mark Sanderson ◽  
...  
Keyword(s):  
Information Retrieval ◽  
Natural Language Processing ◽  
Natural Language ◽  
Human Computer Interaction ◽  
Language Processing ◽  
Research Agenda ◽  
Web Search ◽  
Dialogue Systems ◽  
Future Directions ◽  
Working Groups

In the week of November 10--15, 2019, 44 researchers from the fields of information retrieval and Web search, natural language processing, human computer interaction, and dialogue systems met for the Dagstuhl Seminar 19461 "Conversational Search" to share the latest development in the area of conversational search and discuss its research agenda and future directions. The clear signal from the seminar is that research opportunities to advance conversational search are available to many areas and that collaboration in an interdisciplinary community is essential to achieve the goals. This report overviews the program and selected findings of the working groups.

scholarly journals Dictionaries of Mexican Sexual Slang for NLP

2018 ◽  
Author(s):  
Roberto Villarejo-Martínez ◽  
Noé Alejandro Castro-Sánchez ◽  
Gerardo Sierra Martínez
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Human Computer Interaction ◽  
Language Processing ◽  
User Interfaces ◽  
Scientific Community ◽  
Recognition Problem ◽  
Direct Impact ◽  
Mexican Spanish ◽  
The Creation

Abstract: In this paper the creation of two relevant resources for the double entendre and humour recognition problem in Mexican Spanish is described: a morphological dictionary and a semantic dictionary. These were created from two sources: a corpus of albures (drawn from “Antología del albur” book) and a Mexican slang dictionary (“El chilangonario”). The morphological dictionary consists of 410 forms of words that corresponds to 350 lemmas. The semantic dictionary consists of 27 synsets that are associated to lemmas of morphological dictionary. Since both resources are based on Freeling library, they are easy to implement for tasks in Natural Language Processing. The motivation for this work comes from the need to address problems such as double entendre and computational humour. The usefulness of these disciplines has been discussed many times and it has been shown that they have a direct impact on user interfaces and, mainly, in human-computer interaction. This work aims to promote that the scientific community generates more resources about informal language in Spanish and other languages.  Spanish Abstract: En este artículo se describe la creación de dos recursos relevantes para el reconocimiento del doble sentido y el humor en el español mexicano: un diccionario morfológico y un diccionario semántico. Éstos fueron creados a partir de dos fuentes: un corpus de albures (extraídos del libro "Antología del albur") y un diccionario de argot mexicano ("El chilangonario"). El diccionario morfológico consiste en 410 formas de palabras que corresponden a 350 lemas. El diccionario semántico consiste en 27 synsets que están asociados a lemas del diccionario morfológico. Puesto que ambos recursos están basados en la biblioteca Freeling, son fáciles de implementar en tareas de Procesamiento del Lenguaje Natural. La motivación de este trabajo proviene de la necesidad de abordar problemas como el doble sentido y el humor computacional. La utilidad de estas disciplinas han sido discutidas muchas veces y se ha mostrado que tienen un impacto directo en las interfaces de usuario y, principalmente, en la interacción humano-computadora. Este trabajo tiene como objetivo promover que la comunidad científica genere más recursos sobre el lenguaje informal en español y otros lenguajes. 

A Review and evaluation of Machine Translation methods for Lumasaaba

2020 ◽  
pp. 3-17
Author(s):  
Peter Nabende
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Machine Translation ◽  
Language Processing ◽  
Research Area ◽  
Data Driven ◽  
East African ◽  
Data Set ◽  
African Languages ◽  
Translation Methods

Natural Language Processing for under-resourced languages is now a mainstream research area. However, there are limited studies on Natural Language Processing applications for many indigenous East African languages. As a contribution to covering the current gap of knowledge, this paper focuses on evaluating the application of well-established machine translation methods for one heavily under-resourced indigenous East African language called Lumasaaba. Specifically, we review the most common machine translation methods in the context of Lumasaaba including both rule-based and data-driven methods. Then we apply a state of the art data-driven machine translation method to learn models for automating translation between Lumasaaba and English using a very limited data set of parallel sentences. Automatic evaluation results show that a transformer-based Neural Machine Translation model architecture leads to consistently better BLEU scores than the recurrent neural network-based models. Moreover, the automatically generated translations can be comprehended to a reasonable extent and are usually associated with the source language input.

1243-P: Novel Use of Natural Language Processing to Identify Reasons for Insulin Discontinuation in Patients with T2DM: A Real-World Evidence Study

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 1243-P
Author(s):  
JIANMIN WU ◽  
FRITHA J. MORRISON ◽  
ZHENXIANG ZHAO ◽  
XUANYAO HE ◽  
MARIA SHUBINA ◽  
...  
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Real World ◽  
Real World Evidence

WHO DO WE THINK WE ARE? COMPARING INTERSECTIONAL IDENTITY TRENDS IN ASEE AND CEEA-ACEG USING NATURAL LANGUAGE PROCESSING AND REVIEW OF PROCEEDINGS

2019 ◽  
Author(s):  
Pamela Rogalski ◽  
Eric Mikulin ◽  
Deborah Tihanyi
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Activity Theory ◽  
Language Processing ◽  
Division Of Labour ◽  
Cultural Historical Activity Theory ◽  
Original Question ◽  
Micro Level ◽  
Historical Activity ◽  
Cultural Historical Activity

In 2018, we overheard many CEEA-AGEC members stating that they have "found their people"; this led us to wonder what makes this evolving community unique. Using cultural historical activity theory to view the proceedings of CEEA-ACEG 2004-2018 in comparison with the geographically and intellectually adjacent ASEE, we used both machine-driven (Natural Language Processing, NLP) and human-driven (literature review of the proceedings) methods. Here, we hoped to build on surveys—most recently by Nelson and Brennan (2018)—to understand, beyond what members say about themselves, what makes the CEEA-AGEC community distinct, where it has come from, and where it is going. Engaging in the two methods of data collection quickly diverted our focus from an analysis of the data themselves to the characteristics of the data in terms of cultural historical activity theory. Our preliminary findings point to some unique characteristics of machine- and human-driven results, with the former, as might be expected, focusing on the micro-level (words and language patterns) and the latter on the macro-level (ideas and concepts). NLP generated data within the realms of "community" and "division of labour" while the review of proceedings centred on "subject" and "object"; both found "instruments," although NLP with greater granularity. With this new understanding of the relative strengths of each method, we have a revised framework for addressing our original question.  

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