000			02187nam a2200265Ia 4500
001			77572
003			ft7083
005			20251010152104.0
008			190413n 000 0 eng d
040			_erda
041			_aengtag
050			_aQA76.9 D45 2019
082			_a.
100			_aDequito, Chrisanne Jay P. and Sojuaco, Francesca Mae B.
245		0	_aA mobile application using matrix factorization algorithm for travel itenerary recommendation
264			_aManila: _bPLM, _cc2019
300			_aUndergraduate Thesis: (BS in Computer Science)- Pamantasan ng Lungsod ng Maynila, 2019.
336			_btext _atext _2text
337			_bunmediated _aunmediated _2unmediated
338			_bvolume _avolume _2volume
505			_aABSTRACT: Matrix Factorization Algorithm is a recommendation algorithm derived from Collaborative Filtering. It is popularized and used by Netflix to recommend movies based on the behavior of a certain user. The researchers will apply this algorithm in their Mobile Application for Travel Itinerary Recommendation. The algorithm can intelligently predict the chances of a user on whether he will have interest in a place. Along with these predictions, the mobile application filters the locations according to the budget and time of the user before generating itineraries. The Agile Method will be used in this study because of its iterative nature, for easier revision, and because of short development period. The platform that the researchers used is Ionic Framework for developing mobile application and MySQL using PHPMyAdmin for the database. They also used PHP scripting language to apply the Matrix Factorization Algorithm in the mobile application. To further enhance the performance of the mobile application and to optimize the predicted results, Gradient Descent Algorithm is alsoused. The greatest challenge for the researchers was acquiring data for the dataset, since the amount of data affects the accuracy of the results produced by the algorithm. Ratings on a place is also very valuable because it is one of the bases of the recommendation application.
526			_aF
655			_aenvironmental science
942			_alcc _cMS _2lcc
999			_c25366 _d25366