Specific Touch Gesture on Mobile Devices to Find Attractive Phrases in News Browsing

When smart phone users browse web news articles, they encounter attractive phrases by chance. At that time, they try to obtain information on the smart phones. In order to search the information of the attractive phrases on web pages, they have to manipulate the smart phones to search on the small screen. It causes stresses because of situations such as manipulation errors. Such stresses could be eliminated if the attractive phrases can be identified and be input automatically in order to recommend the web pages with the information of the attractive phrases. Because of the small screens of smart phones, users move the news article area displayed on the screens with touch gestures such as swipe. The history of touch gestures during browsing an article implies the position and the timing users have focused on in the article. This paper proposes a method to identify the areas where attractive phrases have appeared on news articles, in order to enable automatic identification of attractive phrases. We have achieved real-time identification by utilizing the history of touch gestures during a web news browsing. The proposed method shows the history of touch gestures by a gesture trail. It is a graph showing the time series of the vertical coordinate of the displayed article area. When users encounter attractive phrases, they take certain patterns of touch gestures to confirm or read carefully the neighborhood of the attractive phrases. Thus, in the proposed method, the news article area including an attractive phrase is detected by matching the gesture trail in a sliding time window with a pattern obtained by pre-training. We use slow-down and resting patterns approximated by quadratic functions with the parameters defined for individual users. Experiments to identify time windows of attractive phrases on gesture trails has revealed that the highest and the lowest precision ratios are 0.579 and 0.278, respectively.