Startup Rio: User Experience and Startups

Renzi, Adriano Bernardo; Chammas, Adriana; Agner, Luiz; Greenshpan, Jacob

doi:10.1007/978-3-319-20886-2_32

Cited by 7 publications

(3 citation statements)

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“…Subsequently, the blend of the think-a-loud protocol [43]and systems thinking [44] notions are used to collectively brainstorm on the problem of concern and ultimately AIML (Artificial Intelligence-based modelling/mark-up language) is selected to implement the proposed solution, as AIML is recognized as an ideal technology for creating natural language software agents with an XML dialectic [44][45][46][47][48].…”

Section: Methodsmentioning

confidence: 99%

Fully Automated Ontology Increment`S user Guide Generation

Vidanage¹,

Mohemad²,

Noor³

et al. 2021

IJACSA

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This research focuses on a domain and schema independent user-guide generation for ontology increments. Having a user guide or a catalogue/manual is vital for quick and effective knowledge dissemination. If a user guide can be generated for an ontology as well, there could be ample advantages. Stakeholders can scan across the user guide of the ontology and verify the eligibility of it, against the intended purposes. Additionally, this could be useful in ontology`s version management requisites and knowledge verification requirements as well. Even though, ontology construction being iterative and incremental operational, there will be several intermediate versions before it reaches to the fine-tuned final version. Therefore, manual user guide creation will be a tedious and impossible operation. Consequently, this research focuses on a novel algorithmic approach to domain and schema independent ontology verbalization. A special algorithm is created to alter the functionality of Google's AliceBot to work as a verbalizer, instead of a chatterbot. Artificial Intelligent Modelling Language (AIML) technology is utilized to create the templates for the ontology specific knowledge embeddings. This entire process is fully automated via the proposed novel algorithm, which is a key contribution of this research. Eventually, the generated user guide generation tool is evaluated against three different domains with the involvement of fifteen stakeholders and 82% of averaged acceptance has been yielded.

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Section: Methodsmentioning

confidence: 99%

Fully Automated Ontology Increment`S user Guide Generation

Vidanage¹,

Mohemad²,

Noor³

et al. 2021

IJACSA

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show abstract

“…Then, there must be several service providers to answer their needs. In this group, mentors, coaches, trainers and other actors are also included (Renzi et al 2015). -Large companies: Although start-up companies deal with certain ideas to enter into some niche markets, large companies might highly affect their performance.…”

Section: The Start-up Ecosystemmentioning

confidence: 99%

Rapid Internationalization Emerging Markets Multinationals from Latin America: The Case of the AJE Group

Duque-Ruiz

Zuluaga

González-Pérez

2018

Contributions to Management Science

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the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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“…However, for distinct reasons (e.g. costs), counting on evaluators with low expertise (novices) is common among practitioners (FERNAN-DEZ;ABRAHÃO, 2011;RENZI et al, 2015;HUANG, 2012;BRUUN;STAGE, 2014;BRUUN;STAGE, 2015). Similarly to other inspection methods, the HE is dependent on evaluators' knowledge and opinion WOOLRYCH, 2009;WOOLRYCH, 2001).…”

Section: Heuristic Evaluation and Novice Evaluatorsmentioning

confidence: 99%

Adaptations to the Heuristic Evaluation (HE) method for novice evaluators

Salgado¹

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Startup Rio: User Experience and Startups

Cited by 7 publications

References 0 publications

Fully Automated Ontology Increment`S user Guide Generation

Fully Automated Ontology Increment`S user Guide Generation

Rapid Internationalization Emerging Markets Multinationals from Latin America: The Case of the AJE Group

Adaptations to the Heuristic Evaluation (HE) method for novice evaluators

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