SwePub
Sök i LIBRIS databas

  Utökad sökning

id:"swepub:oai:DiVA.org:bth-18592"
 

Sökning: id:"swepub:oai:DiVA.org:bth-18592" > Using conformal pre...

Using conformal prediction for multi-label document classification in e-Mail support systems

Borg, Anton (författare)
Blekinge Tekniska Högskola,Institutionen för datavetenskap
Boldt, Martin (författare)
Blekinge Tekniska Högskola,Institutionen för datavetenskap
Svensson, Johan (författare)
Telenor Sverige AB, SWE
 (creator_code:org_t)
2019-06-15
2019
Engelska.
Ingår i: ADVANCES AND TRENDS IN ARTIFICIAL INTELLIGENCE: FROM THEORY TO PRACTICE. - Cham : Springer Verlag. - 9783030229986 ; , s. 308-322
  • Konferensbidrag (refereegranskat)
Abstract Ämnesord
Stäng  
  • For any corporation the interaction with its customers is an important business process. This is especially the case for resolving various business-related issues that customers encounter. Classifying the type of such customer service e-mails to provide improved customer service is thus important. The classification of e-mails makes it possible to direct them to the most suitable handler within customer service. We have investigated the following two aspects of customer e-mail classification within a large Swedish corporation. First, whether a multi-label classifier can be introduced that performs similarly to an already existing multi-class classifier. Second, whether conformal prediction can be used to quantify the certainty of the predictions without loss in classification performance. Experiments were used to investigate these aspects using several evaluation metrics. The results show that for most evaluation metrics, there is no significant difference between multi-class and multi-label classifiers, except for Hamming loss where the multi-label approach performed with a lower loss. Further, the use of conformal prediction did not introduce any significant difference in classification performance for neither the multi-class nor the multi-label approach. As such, the results indicate that conformal prediction is a useful addition that quantifies the certainty of predictions without negative effects on the classification performance, which in turn allows detection of statistically significant predictions. © Springer Nature Switzerland AG 2019.

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)

Nyckelord

Conformal prediction
Customer support e-mail
Multi-label classification
Electronic mail
Forecasting
Information retrieval systems
Intelligent systems
Sales
Classification performance
Conformal predictions
Customer support
Document Classification
Email classification
Evaluation metrics
Multi label classification
Multi-class classifier
Classification (of information)

Publikations- och innehållstyp

ref (ämneskategori)
kon (ämneskategori)

Hitta via bibliotek

Till lärosätets databas

Hitta mer i SwePub

Av författaren/redakt...
Borg, Anton
Boldt, Martin
Svensson, Johan
Om ämnet
NATURVETENSKAP
NATURVETENSKAP
och Data och informa ...
och Datavetenskap
Artiklar i publikationen
ADVANCES AND TRE ...
Av lärosätet
Blekinge Tekniska Högskola

Sök utanför SwePub

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Stäng

Kopiera och spara länken för att återkomma till aktuell vy