Point of Interest Calculation based on Prefixspan
碩士 === 淡江大學 === 資訊工程學系碩士班 === 104 === The rapid development and popularity of transport technology encourages people to travel frequently. As many traveling experiences are been shared through the Internet,more people are searching interesting sites from different web sites. Traveling informations i...
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ndltd-TW-104TKU053920072017-08-27T04:30:24Z http://ndltd.ncl.edu.tw/handle/54385503119136373380 Point of Interest Calculation based on Prefixspan 基於Prefixspan 演算法結合旅遊景點行程計算 Ying-Yi Lee 李映宜 碩士 淡江大學 資訊工程學系碩士班 104 The rapid development and popularity of transport technology encourages people to travel frequently. As many traveling experiences are been shared through the Internet,more people are searching interesting sites from different web sites. Traveling informations including itinerary and accomodations are scattered and it is not easy to grasp relevant information. Especially when people want information regarding to regions where they never been to before, questions such as the most popular attractions, and what are the restaurant most visited are not easy to answer. In order to answer the above questions, efficient methods in combining and calculating the large amount of traveling informations are needed. This thesis address the issue by comparing different algorithms in calculating point of interest. The result showed prefixspan is more efficient than aprioriall in a modern day Hadoop computation platform. 蔡憶佳 2016 學位論文 ; thesis 53 zh-TW |
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碩士 === 淡江大學 === 資訊工程學系碩士班 === 104 === The rapid development and popularity of transport technology encourages people to travel frequently.
As many traveling experiences are been shared through the Internet,more people are searching interesting sites from different web sites. Traveling informations including itinerary and accomodations are scattered and it is not easy to grasp relevant information. Especially when people want information regarding to regions where they never been to before, questions such as the most popular attractions, and what are the restaurant most visited are not easy to answer.
In order to answer the above questions, efficient methods in combining and calculating the large amount of traveling informations are needed. This thesis address the issue by comparing different algorithms in calculating point of interest. The result showed prefixspan is more efficient than aprioriall in a modern day Hadoop computation platform.
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蔡憶佳 |
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蔡憶佳 Ying-Yi Lee 李映宜 |
author |
Ying-Yi Lee 李映宜 |
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Ying-Yi Lee 李映宜 Point of Interest Calculation based on Prefixspan |
author_sort |
Ying-Yi Lee |
title |
Point of Interest Calculation based on Prefixspan |
title_short |
Point of Interest Calculation based on Prefixspan |
title_full |
Point of Interest Calculation based on Prefixspan |
title_fullStr |
Point of Interest Calculation based on Prefixspan |
title_full_unstemmed |
Point of Interest Calculation based on Prefixspan |
title_sort |
point of interest calculation based on prefixspan |
publishDate |
2016 |
url |
http://ndltd.ncl.edu.tw/handle/54385503119136373380 |
work_keys_str_mv |
AT yingyilee pointofinterestcalculationbasedonprefixspan AT lǐyìngyí pointofinterestcalculationbasedonprefixspan AT yingyilee jīyúprefixspanyǎnsuànfǎjiéhélǚyóujǐngdiǎnxíngchéngjìsuàn AT lǐyìngyí jīyúprefixspanyǎnsuànfǎjiéhélǚyóujǐngdiǎnxíngchéngjìsuàn |
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1718519496008794112 |