2Es of TIS
Tourism industry could be one of the largest sources of revenue for any country. After the emergence of Web 2.0, it is also one of the largest data intensive industries in the world. Tourism‐rich countries often use Tourism Information Systems (TIS) for management of tourism‐related data. These syst...
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| creator | Missen, Malik M. Saad Coustaty, Mickaël Asmat, Hina Firdous, Amnah Akhtar, Nadeem Akram, Muhammad Prasath, V. B. Surya |
| description | Tourism industry could be one of the largest sources of revenue for any country. After the emergence of Web 2.0, it is also one of the largest data intensive industries in the world. Tourism‐rich countries often use Tourism Information Systems (TIS) for management of tourism‐related data. These systems are used are used on several levels of tourism stakeholder's hierarchy from data generation and exchange to intelligent decision making. Data exchange and extraction are core tasks that a generic TIS is supposed to perform. In this chapter, we discuss both of these processes with respect to TIS. We describe the importance of these processes and review how these are being dealt by researchers currently. Further, we highlight the limitations of current approaches of data exchange and extraction and identify potent future solutions that can enhance the performance of TIS in many aspects can drive future recommender systems. |
| doi_str_mv | 10.1002/9781119711582.ch3 |
| format | Book Chapter |
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Surya</creator><contributor>Jain, Sarika ; Chatterjee, Jyotir Moy ; Gupta, Priya ; Elngar, Ahmed A ; Mohanty, Sachi Nandan</contributor><creatorcontrib>Missen, Malik M. Saad ; Coustaty, Mickaël ; Asmat, Hina ; Firdous, Amnah ; Akhtar, Nadeem ; Akram, Muhammad ; Prasath, V. B. Surya ; Jain, Sarika ; Chatterjee, Jyotir Moy ; Gupta, Priya ; Elngar, Ahmed A ; Mohanty, Sachi Nandan</creatorcontrib><description>Tourism industry could be one of the largest sources of revenue for any country. After the emergence of Web 2.0, it is also one of the largest data intensive industries in the world. Tourism‐rich countries often use Tourism Information Systems (TIS) for management of tourism‐related data. These systems are used are used on several levels of tourism stakeholder's hierarchy from data generation and exchange to intelligent decision making. Data exchange and extraction are core tasks that a generic TIS is supposed to perform. In this chapter, we discuss both of these processes with respect to TIS. We describe the importance of these processes and review how these are being dealt by researchers currently. 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Saad</creatorcontrib><creatorcontrib>Coustaty, Mickaël</creatorcontrib><creatorcontrib>Asmat, Hina</creatorcontrib><creatorcontrib>Firdous, Amnah</creatorcontrib><creatorcontrib>Akhtar, Nadeem</creatorcontrib><creatorcontrib>Akram, Muhammad</creatorcontrib><creatorcontrib>Prasath, V. B. Surya</creatorcontrib></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Missen, Malik M. Saad</au><au>Coustaty, Mickaël</au><au>Asmat, Hina</au><au>Firdous, Amnah</au><au>Akhtar, Nadeem</au><au>Akram, Muhammad</au><au>Prasath, V. B. Surya</au><au>Jain, Sarika</au><au>Chatterjee, Jyotir Moy</au><au>Gupta, Priya</au><au>Elngar, Ahmed A</au><au>Mohanty, Sachi Nandan</au><format>book</format><genre>bookitem</genre><ristype>CHAP</ristype><atitle>2Es of TIS</atitle><btitle>Recommender System with Machine Learning and Artificial Intelligence</btitle><date>2020-06-17</date><risdate>2020</risdate><spage>45</spage><epage>70</epage><pages>45-70</pages><isbn>9781119711575</isbn><isbn>1119711576</isbn><eisbn>1119711584</eisbn><eisbn>9781119711582</eisbn><abstract>Tourism industry could be one of the largest sources of revenue for any country. After the emergence of Web 2.0, it is also one of the largest data intensive industries in the world. Tourism‐rich countries often use Tourism Information Systems (TIS) for management of tourism‐related data. These systems are used are used on several levels of tourism stakeholder's hierarchy from data generation and exchange to intelligent decision making. Data exchange and extraction are core tasks that a generic TIS is supposed to perform. In this chapter, we discuss both of these processes with respect to TIS. We describe the importance of these processes and review how these are being dealt by researchers currently. Further, we highlight the limitations of current approaches of data exchange and extraction and identify potent future solutions that can enhance the performance of TIS in many aspects can drive future recommender systems.</abstract><cop>Hoboken, NJ, USA</cop><pub>John Wiley & Sons, Inc</pub><doi>10.1002/9781119711582.ch3</doi><tpages>26</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISBN: 9781119711575 |
| ispartof | Recommender System with Machine Learning and Artificial Intelligence, 2020, p.45-70 |
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| language | eng |
| recordid | cdi_wiley_ebooks_10_1002_9781119711582_ch3_ch3 |
| source | O'Reilly Online Learning: Academic/Public Library Edition |
| subjects | information exchange Information extraction opinion extraction tourism information system tourism tecommender system |
| title | 2Es of TIS |
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