Automatic linguistic reporting of customer activity patterns in open malls
| Autor: | Miguel Ángel García-Garrido, David Chapela-Campa, Pedro Álvarez, Manuel Ocaña, Noelia Hernández, Alberto Bugarín, P. Revenga, Ángel Llamazares, Manuel Mucientes, Manuel Lama, Jose M. Alonso, Javier Fabra |
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| Přispěvatelé: | Universidade de Santiago de Compostela. Centro de Investigación en Tecnoloxías da Información, Universidade de Santiago de Compostela. Departamento de Electrónica e Computación |
| Rok vydání: | 2021 |
| Předmět: |
Computer Networks and Communications
Computer science media_common.quotation_subject Automatic linguistic reporting Process mining 02 engineering and technology Computer-assisted web interviewing Likert scale 030507 speech-language pathology & audiology 03 medical and health sciences Social workflows 0202 electrical engineering electronic engineering information engineering Media Technology Quality (business) Dimension (data warehouse) media_common Natural language generation Linguistics Data mining techniques Visualization Hardware and Architecture Localization 020201 artificial intelligence & image processing Parallelization strategies 0305 other medical science Software Natural language |
| Zdroj: | Multimedia Tools and Applications. 81:3369-3395 |
| ISSN: | 1573-7721 1380-7501 |
| Popis: | In this work, we present a complete system to produce an automatic linguistic reporting about the customer activity patterns inside open malls, a mixed distribution of classical malls joined with the shops on the street. These reports can assist to design marketing campaigns by means of identifying the best places to catch the attention of customers. Activity patterns are estimated with process mining techniques and the key information of localization. Localization is obtained with a parallelized solution based on WiFi fingerprint system to speed up the solution. In agreement with the best practices for human evaluation of natural language generation systems, the linguistic quality of the generated report was evaluated by 41 experts who filled in an online questionnaire. Results are encouraging, since the average global score of the linguistic quality dimension is 6.17 (0.76 of standard deviation) in a 7- point Likert scale. This expresses a high degree of satisfaction of the generated reports and validates the adequacy of automatic natural language textual reports as a complementary tool to process model visualization This work has been partially supported by the Spanish Ministry of Science Innovation and Universities and the European Regional Development Fund (ERDF/FEDER) Grants RTI2018-099646-BI00, TIN2017-84796-C2-1-R, TIN2017-90773-REDT, RED2018-102641-T and RYC-2016-19802 (Ramón y Cajal program, José M. Alonso). Also by the Galician Ministry of Education, University and Professional Training and the ERDF/FEDER program (ED431F2018/02, ED431C2018/29, ED431G2019/04 grants) SI |
| Databáze: | OpenAIRE |
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