Semi-autonomous methodology to validate and update customer needs database through text data analytics
Document identifier: oai:DiVA.org:ltu-77834
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10.1016/j.ijinfomgt.2020.102073Keyword: Engineering and Technology,
Mechanical Engineering,
Applied Mechanics,
Teknik och teknologier,
Maskinteknik,
Teknisk mekanik,
Other Mechanical Engineering,
Annan maskinteknik,
Customer need,
CN,
Company knowledge,
Text data,
Machine Design,
Maskinkonstruktion,
Computer Aided Design,
Datorstödd maskinkonstruktionPublication year: 2020Relevant Sustainable Development Goals (SDGs):
The SDG label(s) above have been assigned by OSDG.aiAbstract: To develop highly competitive products, companies need to understand customer needs (CNs) by effectively gathering and analysing customer data. With the advances in Information Technology, customer data comes not only from surveys and focus groups but also from social media and networking sites. Few studies have focused on developing algorithms that are devised exclusively to help to understand customer needs from big opinion data. Topic mining, aspect-based sentiment analysis and word embedding are some of the techniques adopted to identify CNs from text data. However, most of them do not consider the possibility that part of the customer data analysed is already known by companies. With the aim to continuously enhance company understanding of CNs, this paper presents an autonomous methodology for automatically classifying a set of text data (customer sentences) as referring to known or unknown CN statements by the company. For verification purposes, an example regarding a set of customer answers from an open survey questionnaire regarding the climate system of a car is illustrated. Results indicate that the proposed methodology helps companies to validate and update the customer need database with an average of 90 % precision and 60 % recall.
Authors
Anna Marti Bigorra
Luleå tekniska universitet; Produkt- och produktionsutveckling
Other publications
>>
Ove Isaksson
Hydcon KB, Sweden
Other publications
>>
Magnus Karlberg
Luleå tekniska universitet; Produkt- och produktionsutveckling
Other publications
>>
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identifier: oai:DiVA.org:ltu-77834
datestamp: 2021-04-19T12:42:23Z
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recordCreationDate: 2020-02-24
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10.1016/j.ijinfomgt.2020.102073
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titleInfo:
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lang: eng
title: Semi-autonomous methodology to validate and update customer needs database through text data analytics
abstract: To develop highly competitive products companies need to understand customer needs (CNs) by effectively gathering and analysing customer data. With the advances in Information Technology customer data comes not only from surveys and focus groups but also from social media and networking sites. Few studies have focused on developing algorithms that are devised exclusively to help to understand customer needs from big opinion data. Topic mining aspect-based sentiment analysis and word embedding are some of the techniques adopted to identify CNs from text data. However most of them do not consider the possibility that part of the customer data analysed is already known by companies. With the aim to continuously enhance company understanding of CNs this paper presents an autonomous methodology for automatically classifying a set of text data (customer sentences) as referring to known or unknown CN statements by the company. For verification purposes an example regarding a set of customer answers from an open survey questionnaire regarding the climate system of a car is illustrated. Results indicate that the proposed methodology helps companies to validate and update the customer need database with an average of 90 % precision and 60 % recall.
subject:
@attributes:
lang: eng
authority: uka.se
topic:
Engineering and Technology
Mechanical Engineering
Applied Mechanics
@attributes:
lang: swe
authority: uka.se
topic:
Teknik och teknologier
Maskinteknik
Teknisk mekanik
@attributes:
lang: eng
authority: uka.se
topic:
Engineering and Technology
Mechanical Engineering
Other Mechanical Engineering
@attributes:
lang: swe
authority: uka.se
topic:
Teknik och teknologier
Maskinteknik
Annan maskinteknik
@attributes:
lang: eng
topic: Customer need
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lang: eng
topic: CN
@attributes:
lang: eng
topic: Company knowledge
@attributes:
lang: eng
topic: Text data
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lang: eng
authority: ltu
topic: Machine Design
genre: Research subject
@attributes:
lang: swe
authority: ltu
topic: Maskinkonstruktion
genre: Research subject
@attributes:
lang: eng
authority: ltu
topic: Computer Aided Design
genre: Research subject
@attributes:
lang: swe
authority: ltu
topic: Datorstödd maskinkonstruktion
genre: Research subject
language:
languageTerm: eng
genre:
publication/journal-article
ref
note:
Published
3
Validerad;2020;Nivå 2;2020-04-20 (alebob)
name:
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type: personal
authority: ltu
namePart:
Marti Bigorra
Anna
1990-
role:
roleTerm: aut
affiliation:
Luleå tekniska universitet
Produkt- och produktionsutveckling
nameIdentifier:
mannar
0000-0001-7918-003x
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namePart:
Isaksson
Ove
role:
roleTerm: aut
affiliation: Hydcon KB Sweden
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authority: ltu
namePart:
Karlberg
Magnus
role:
roleTerm: aut
affiliation:
Luleå tekniska universitet
Produkt- och produktionsutveckling
nameIdentifier:
magkar
0000-0002-2342-1647
originInfo:
dateIssued: 2020
publisher: Elsevier
relatedItem:
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type: host
titleInfo:
title: International Journal of Information Management
identifier:
0268-4012
1873-4707
part:
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type: volume
number: 52
@attributes:
type: artNo
number: 102073
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