Abstract
Determining traveling routes that provide opportunities to satisfy the various requirements of users in urban areas is still an open problem. This is because it is virtually impossible to manually quantify the characteristics of each street or road and there are few web-based or semantic resources of subjective requirements that describe streets and roads directly. Thus, it is difficult to satisfy all the needs and desires of users that may arise, such as for finding boulevards that are “fashionable” or “beautiful.” The goal of this study is to automatically quantify the characteristics of streets and roads in relation to requirements that can be described using keywords such as “fashionable.” To achieve this goal, we propose a two-stage method that analyzes social media and road networks. First, in estimating the topic distribution (i.e., the characteristics) of each point of interest (POI), our method uses the latent Dirichlet allocation model to analyze geo-tagged texts while considering which users posted useful information for estimating road characteristics. Next, it uses a Markov random field model to estimate the characteristics of each street or road on the basis of those of the POIs and the road networks associated with the POIs. Experiments on real datasets demonstrate that our method achieves statistically significant improvements over baseline methods in terms of ranking quality in information retrieval for 300 roads in three urban areas in Tokyo when given 25 keywords.
Highlights
Lynch (1960) noted that paths are often the most important elements in people’s image of their city
For realizing a novel new route navigation service that can satisfy various user demands, we tackled the problem of quantifying road characteristics, which was shown to be an important task by our user survey
The difficulty of quantifying road characteristics is the lack of sufficient quantitative data associated with the road characteristics that correspond to all user possible requirements and desires
Summary
Lynch (1960) noted that paths are often the most important elements in people’s image of their city. Their images of paths consist of different points of view as regards geographical characteristics. Recent route navigation services provide path-finding functions that consider just a few basic characteristics, such as ease of walking, in addition to path length. User desires with regard to traveling routes are much more varied, and the existing services fail to consider most of them. The results of our private survey on user requirements show that there are about 900 distinct types (road characteristics) associated with traveling routes. Some users want to walk along fashionable streets or roads that offer currently popular styles of clothing. Other users want quiet and beautiful paths, while others want to walk through streets with lively atmospheres
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