An exploration of ranking heuristics in mobile local search

Users increasingly rely on their mobile devices to search local entities, typically businesses, while on the go. Even though recent work has recognized that the ranking signals in mobile local search (e.g., distance and customer rating score of a business) are quite different from general Web search, they have mostly treated these signals as a black-box to extract very basic features (e.g., raw distance values and rating scores) without going inside the signals to understand how exactly they affect the relevance of a business. However, as it has been demonstrated in the development of general information retrieval models, it is critical to explore the underlying behaviors/heuristics of a ranking signal to design more effective ranking features. In this paper, we follow a data-driven methodology to study the behavior of these ranking signals in mobile local search using a large-scale query log. Our analysis reveals interesting heuristics that can be used to guide the exploitation of...

• Type: Journal
• Year: 2012
• Where: SIGIR
• Authors: Yuanhua Lv, Dimitrios Lymberopoulos, Qiang Wu
• Keywords: Information Retrieval Models, Information Technology, Search Logs, SIGIR 2012, Transformation Methods