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PlaceRank: A system and method to rank importance of inter-connected places

IP.com Disclosure Number: IPCOM000237494D
Publication Date: 2014-Jun-19
Document File: 6 page(s) / 114K

Publishing Venue

The IP.com Prior Art Database

Abstract

Human beings can naturally interpret the "importance'' of a place or a region based on various factors such as its neighborhood, the connectivity infrastructure, etc. The importance of a region in turn plays a critical role in various decision policies such as development of business districts, residential complexes, and targeting locations for promotional campaigns. While such developmental decisions are routinely taken based on subjective opinions of personnel involved, currently, no system exists that can quantify and rank the importance of a region based on some provided meta-information characterizing its properties and its relationship with other regions in the neighborhood. An automated system to quantify the importance of a region is critical towards capturing the highly complex relationships that exist between various factors that influence its importance. Additionally, the importance of a place is not only dependent on its own attributes, but also on its connectivity to other regions. (For example, the construction of a residential complex changes the importance of neighboring places which would influence subsequent decision policies such as building schools, malls, etc.) Furthermore, the importance of a place changes with time; while quality of buildings decay with time, construction of new roads and upgradation of infrastructure raise the importance. To tackle these natural dynamicity, an automated system is required to adapt and update the importance of a place in a consistent and systematic manner.

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PlaceRank: A system and method to rank importance of inter -connected places


1. Abstract and Background:

    Human beings can naturally interpret the "importance'' of a place or a region based on various factors such as its neighborhood, the connectivity infrastructure, etc. The importance of a region in turn plays a critical role in various decision policies such as development of business districts, residential complexes, and targeting locations for promotional campaigns. While such developmental decisions are routinely taken based on subjective opinions of personnel involved, currently, no system exists that can quantify and rank the importance of a region based on some provided meta-information characterizing its properties and its relationship with other regions in the neighborhood.

    An automated system to quantify the importance of a region is critical towards capturing the highly complex relationships that exist between various factors that influence its importance. Additionally, the importance of a place is not only dependent on its own attributes, but also on its connectivity to other regions. (For example, the construction of a residential complex changes the importance of neighboring places which would influence subsequent decision policies such as building schools, malls, etc.) Furthermore, the importance of a place changes with time; while quality of buildings decay with time, construction of new roads and upgradation of infrastructure raise the importance. To tackle these natural dynamicity, an automated system is required to adapt and update the importance of a place in a consistent and systematic manner.

Several applications can utilize the place importance ranks. A few of them are given below:

1. Predicting the impact of a development project and its cascading effects on the region so that pre-cautionary measures can be taken in advance.

2. Prioritizing developmental activities, so that the importance of a place can be raised by improving connectivity or infrastructure, and the population in a city can in turn be better distributed.

3. Determining places/regions that have poor reachability under the parameters of weather conditions and natural disasters (e.g., floods, storms, and so on)

This article is geared towards quantifying the importance of inter-connected places and generating a ranked list. Specifically, our core ideas can be described as follows:


 Compute the individual importance of each place based on an application-specific utility function. The definition of a place is application dependent. In essence, a place describes a spatially connected region which makes semantic sense for the application under study.


 Construct an Importance Graph (IG) where each node corresponds to a place and an edge corresponds to a road segment connecting two places. Each node contains information regarding the quality of the place and each edge models the strength of the application-dependent connection between its two...