Outfit Recommender System

The online apparel retail market size in the United States is worth about seventy-two billion US dollars. Recommendation systems on retail websites generate a lot of this revenue. Thus, improving recommendation systems can increase their revenue. Traditional recommendations for clothes consisted of lexical methods. However, visual-based recommendations have gained popularity over the past few years. This involves processing a multitude of images using different image processing techniques. In order to handle such a vast quantity of images, deep neural networks have been used extensively. With the help of fast Graphics Processing Units, these networks provide results which are extremely accurate, within a small amount of time. However, there are still ways in which recommendations for clothes can be improved. We propose an event-based clothing recommendation system which uses object detection. We train a model to identify nine events/scenarios that a user might attend: White Wedding, Indian Wedding, Conference, Funeral, Red Carpet, Pool Party, Birthday, Graduation and Workout. We train another model to detect clothes out of fifty-three categories of clothes worn at the event. Object detection gives a mAP of 84.01. Nearest neighbors of the clothes detected are recommended to the user

Ontology design based on data family planning field officer using OWL and RDF

Population density in Indonesia is ranked fourth in the world. The impact of a large population will affect the level of welfare of the community to decrease, and the number of unemployment is increasing so that the state makes Family Planning Program (PLKB) to control the rate of population growth. Problems in the PLKB program are on knowledge management and mapping from data contraception, counseling and planning so that this research using Ontology method will aim to do mapping with knowledge management and Ontology design shows represented data to relate and describes the resources contained in family planning data. This research approach the representation of ontology that is validated through model transformation from family planning data to ontology design using OWL and RDF which are useful for data processing and representing data to be utilized by field officers in educating the public and eradicating negative issues about family planning program