Title

Mobile social recommender system for travelers

Date of Publication

2009

Document Type

Bachelor's Thesis

Degree Name

Bachelor of Science in Computer Science

Subject Categories

Computer Sciences

College

College of Computer Studies

Department/Unit

Computer Science

Thesis Adviser

Danny C. Cheng

Abstract/Summary

Recommender systems provide options for people that are faced with overwhelming information. Social recommender systems are systems suited on giving recommendation for taste related domains like food, music, clothing and others. This type of domain is greatly influenced by social factors like friends. Thus, this system considers user's peers in giving recommendation. These social recommender systems are now implemented in mobile devices to give way for the demand of remote users like travelers who need recommendations while they are on the go.

Since the common activity of most travelers is taking of photos which serve as their souvenir to remind them of the beautiful places they have been to, the system makes use of these travel photos to gather data needed for recommendation such as the places users' peers have been to. The problem arises when a place is named differently by different travelers or users in the community. Unlike other recommender systems that focus on coming up with methods on gathering and ranking of recommendations, the proposed system focuses on disambiguating the place names gathered across different users by utilizing the user's social network as well as their photo management activities.

Abstract Format

html

Language

English

Format

Print

Accession Number

TU19868

Shelf Location

Archives, The Learning Commons, 12F, Henry Sy Sr. Hall

Physical Description

1 v. (various foliations) : illustrations (some colored) ; 28 cm.

Keywords

Tourism--Computer network resources; Recommender systems (Information filtering)

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