2. Conversational ag...

نتيجة التلخيص (10%)

2.Recently, another systematic literature review of conversational
agents focused on health care was published ( Laranjo et al., 2018 ).This technique is focused mainly on signal processing,
syntactic and semantic analysis of discourse, and pragmatics,
thus allowing natural language generation to provide meaningful
conversation based on context analysis ( Ganesh, Harsha, Pingali, &
Verma, 2008 ).Conversational agents may be considered virtual avatars with
verbal or non-verbal communication characteristics, executing a
human-to-machine interactive task ( Wargnier et al., 2015 ).2.1.

النص الأصلي

Conversational agents
One premise of conversational agents is engagement, which is
defined as a conversational process between agents and users. This
process should observe and analyze the behavior of other participants
with voice or visual tools helping to focus the attention of
individuals on communication. In this sense, conversational agents
execute a vital role in facilitating engagement, which is a major
goal of the technology developer ( Wargnier et al., 2015 ).
Conversational agents may be considered virtual avatars with
verbal or non-verbal communication characteristics, executing a
human-to-machine interactive task ( Wargnier et al., 2015 ). Also
called relational agents, they can emulate some human characteristics,
using different types of interactions such as speech, gaze,
hand gestures, and other nonverbal modalities ( Wang et al., 2015 ).
These types of interactions are called multimodal communication,
being very useful in the health field by providing potential personal
interfaces to interact with users from the health care domain
( Turunen et al., 2011 ).
In the health context, the use of agents for education has been
widely explored, with several applications having been introduced
in the therapeutic and patient care context ( Wang et al., 2015 ).
Robots have been tested continuously for elderly care with features
that support physicians by providing advice and insights to
treat elderly patients ( Heerink, Kröse, Evers, & Wielinga, 2010 ).
Conversational agents act in any environment to gather information
and use it in their interactions through knowledge engineering
processes ( López, Eisman, & Castro, 2008 ). This gathering
process can allow an agent to perform different functions based
on the current necessity, e.g., some studies used speech and language
techniques to detect dementia in patients ( Aramaki, Shikata,
Miyabe, & Kinoshita, 2016; Fraser, Meltzer, & Rudzicz, 2016; Tanaka
et al., 2017a ).
In this sense agents are helpful tools for human-machine interaction,
allowing the input of data via natural language, processing
sentences, and returning answers accurately through text or speech
( Galvao, Barros, Neves, & Ramalho, 2004 ). Some agents apply probabilistic
techniques to improve dialog. Natural language processing
(NLP) is one of the primary tools for interactions between humans
and agents. This technique is focused mainly on signal processing,
syntactic and semantic analysis of discourse, and pragmatics,
thus allowing natural language generation to provide meaningful
conversation based on context analysis ( Ganesh, Harsha, Pingali, &
Verma, 2008 ). In this way, conversational agents can be successful
in creating an informal connection with their users ( Iftene &
Vanderdonckt, 2016 ).
Therefore, conversational agents can use artificial intelligence
algorithms to interpret user dialog and conduct useful interactions
with users. Approaches such as reinforcement learning have gained
popularity in the conversational agents field, demonstrating better
results than approaches based on rules and other techniques
( Yasavur et al., 2014 ).
2.1. Related work
Articles related to the context of our study are presented
in the following review. The survey by Abdul-Kader and
Woods (2015) discussed different techniques, architectures designs,
and methods from papers related to speech interactions through
conversational agents, identifying significant improvements in this
area over the past decade.
Architectures have become a common research topic in the last
few years. The study by D’Alfonso et al. (2017) presented a multimodal
semantic architecture based on ontologies and inferences.
In D’Haro et al. (2017) the focus was develop a modular platform
to combine different types of technologies to provide testing and
checking. Conversational agents play an essential role in integration
with other technologies in this architecture.
In the study by Kar and Haldar (2016) , an architecture involving
the Internet of Things (IoT) and conversational agents was proposed
to identify the challenges and shortcomings of existing IoT
systems.
Recently, another systematic literature review of conversational
agents focused on health care was published ( Laranjo et al., 2018 ).
The study presents specific characteristics of conversational agents,
posing research questions toward the health domain by assessing
aspects including main characteristics and study methods. In this
sense, there are some critical differences with our study. In their
article, the focus is more specific to the health field than on the intersection
of health and computer science. For instance, their survey
does not include many articles on computer science, which is
reflected in the final corpus of 40 articles in our survey and 17 in
theirs. Furthermore, our proposed taxonomy is more comprehensive,
expanding on the agent and architecture aspects, and details
systems and techniques used by conversational agents. Finally, the
research questions aim to elucidate some aspects different from
the other study, including goals, main contexts, and proposals in
the health domain.
According to several research results, and considering the related
work, this article answers the central question: What are the
main interactions, architectures, and dialogues that involve conversational
agents? In this sense, this article aims to develop a systematic
literature review of conversational agents in health care to
better understand the concepts, challenges, goals, types of interactions,
and contexts related to this subject.

آخر التلخيصات

Introduction (S...

Introduction (Sabouraud Dextrose Agar (SDA)). The Sabouraud Dextrose Agar (SDA) or Sabouraud agar me...

‎منهج الإمام ال...

‎منهج الإمام الترمذي المتعلق بالأسانيد ‎أولا: شروطه في أسانيد سننه: ‎1- عمل العلماء بالحديث: كان الم...

ومحوريا في النش...

ومحوريا في النشاط المالي للمؤسسة االقتصادية وذلك نظرا لتأثيره على مختلف أنشطة المؤسسة وخاصة من ناحية...

المرافق لمشروع ...

المرافق لمشروع قانون المالية لسنة 2024 يندرج مشروع قانون المالية لسنة 2024 في سياق اقتصادي ومالي اس...

the choice of c...

the choice of construction materials carries a strong meaning. On the one hand, installing grey bric...

الجيل القلق ......

الجيل القلق .... كيف شوهته الأجهزة الإلكترونية الحالات المستعصية في أميركا ارتفعت 134 % منذ 2010 س...

المبحث الأول: م...

المبحث الأول: مفاهيم حول حوادث المرور وأسبابها المطلب الأول: تعريف الحادث المروري تعريف الحادث المر...

TAXONOMY & ITS ...

TAXONOMY & ITS IMPORTANCE Taxonomy is the science of classifying organisms. The word "Taxono...

أسباب تعاطي الم...

أسباب تعاطي المخدرات النفسية: الحالة النفسية للشخص وما يتخللها من تقلبات مزاجية هي أبرز الأسباب التي...

Evaluation: a. ...

Evaluation: a. Pre- and Post-Program Assessments: Administer surveys to participants before and afte...

مصادر أخرى للدخ...

مصادر أخرى للدخل : بخلاف المصادر السابقة للدخل من ممكن لأفراد تحقيق مداخل من مصادر إضافية ولكنها تتص...

للغة والنمو الل...

للغة والنمو اللغوى لدى األطفال ،تعد اللغة من الميزات اإلنسانية للتواصل ،وأرائد وما يدور فى ذهنه من ...

لخّصلي

نتيجة التلخيص (10%)

النص الأصلي

تلخيص النصوص العربية والإنجليزية أونلاين

آخر التلخيصات