Insights from a text mining survey on Expert Systems research from 2000 to 2016

Cortez, Paulo; Moro, Sérgio; Rita, Paulo; King, David; Hall, Jon G.

doi:10.1111/exsy.12280

Cited by 29 publications

(23 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Cortez et al [205] focused on analyzing 488 research articles published on a specific journal within a 17-year timeline on the domain of expert systems. The authors adopted LDA and followed a methodology similar to that applied by Moro et al [202] and Moro and Rita [206] for branding strategies on social media platforms in the hospitality and tourism field.…”

Section: Published Articlesmentioning

confidence: 99%

Text Mining in Big Data Analytics

Hassani

Beneki

Unger

et al. 2020

BDCC

203

View full text Add to dashboard Cite

Text mining in big data analytics is emerging as a powerful tool for harnessing the power of unstructured textual data by analyzing it to extract new knowledge and to identify significant patterns and correlations hidden in the data. This study seeks to determine the state of text mining research by examining the developments within published literature over past years and provide valuable insights for practitioners and researchers on the predominant trends, methods, and applications of text mining research. In accordance with this, more than 200 academic journal articles on the subject are included and discussed in this review; the state-of-the-art text mining approaches and techniques used for analyzing transcripts and speeches, meeting transcripts, and academic journal articles, as well as websites, emails, blogs, and social media platforms, across a broad range of application areas are also investigated. Additionally, the benefits and challenges related to text mining are also briefly outlined.

show abstract

Section: Published Articlesmentioning

confidence: 99%

Text Mining in Big Data Analytics

Hassani

Beneki

Unger

et al. 2020

BDCC

203

View full text Add to dashboard Cite

show abstract

“…Robotics is understood in this research as the physical ability to move objects following the definition of Russell and Norvig (2016). Expert systems represent algorithm-based programs (Buchanan 1986) offering promising solutions for decision making as well as process automation and contain components for knowledge building, problem solving and communicating solutions based on machine learning (Cortez et al 2018;Turban and Watkins 1986).…”

Section: Application Fields Of Ai Capabilitiesmentioning

confidence: 99%

AI and robotics in the European restaurant sector: Assessing potentials for process innovation in a high-contact service industry

Blöcher

Alt

2020

Electron Markets

View full text Add to dashboard Cite

The restaurant technology market is rapidly evolving and is transforming the restaurant business as a significant sector of tourism and hospitality. Enabled by artificial intelligence (AI), mobile apps, kiosks and chatbots revolutionize the guest experience and robots automate restaurant operations. Despite the increasing interest, the use of AI and robotics in restaurants is still in its early stage and restaurant managers are seeking guidance to leverage these technologies for service excellence. In this high-contact service sector, emotional skills need to be balanced with the possible automation potentials. The present research analyzes the current state of AI and robotics in the restaurant sector and proposes a systematic identification of process innovation potentials. For this purpose, a market analysis of the European AI and robotics market for restaurant operations is conducted, which yields a first knowledge base for future research and conceptual work. Besides detailed empirical data, a reference process is developed for leveraging new technologies for process innovation.

show abstract

“…Therefore, an approach based on standard text mining techniques can be an alternative to automatically select those articles that are relevant to the studied subject (Moro et al 2019), and help in defining and executing inclusion criteria. This approach consists in identifying a lexicon that enables to correctly categorize each article, and then in running a text mining script that builds a document-term matrix that quantifies how many times each of the terms from the lexicon occurs within each article (Cortez et al 2018). Although the lexicon definition is subjective, after it is completed, the computational parsing process of each text is the same regardless of the article.…”

Section: Inclusion Criteriamentioning

confidence: 99%

Empowered learning through microworlds and teaching methods: a text mining and meta-analysis-based systematic review

Costa

Moro

Miranda

et al. 2020

Research in Learning Technology

Self Cite

View full text Add to dashboard Cite

Microworlds are simulations in computational environments where the student can manipulate objects and learn from those manipulations. Since their creation, they have been used in a wide range of academic areas to improve students learning from elementary school to college. However, their effectiveness is unclear since many studies do not measure the acquired knowledge after the use of microworlds but instead they focus on self-evaluation. Furthermore, it has not been clear whether its effect on learning is related to the teaching method. In this study, we perform a meta-analysis to ascertain the impact of microworlds combined with different teaching methods on students’ knowledge acquisition. We applied a selection criterion to a collection of 668 studies and were left with 10 microworld applications relevant to our learning context. These studies were then assessed through a meta-analysis using effect size with Cohen’s d and p-value. Our analysis shows that the cognitive methods combined with microworlds have a great impact on the knowledge acquisition (d = 1.03; p < 0.001) but failed to show a significant effect (d = 0.21) for expository methods.

show abstract

Insights from a text mining survey on Expert Systems research from 2000 to 2016

Cited by 29 publications

References 29 publications

Text Mining in Big Data Analytics

Text Mining in Big Data Analytics

AI and robotics in the European restaurant sector: Assessing potentials for process innovation in a high-contact service industry

Empowered learning through microworlds and teaching methods: a text mining and meta-analysis-based systematic review

Contact Info

Product

Resources

About