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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Main Authors: Ying-Yi Lee, 李映宜
Other Authors: 蔡憶佳
Format: Others
Language:zh-TW
Published: 2016
Online Access:http://ndltd.ncl.edu.tw/handle/54385503119136373380
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spelling 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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language zh-TW
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description 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.
author2 蔡憶佳
author_facet 蔡憶佳
Ying-Yi Lee
李映宜
author Ying-Yi Lee
李映宜
spellingShingle 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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