With the rapid development of mobile Internet technology, on-demand car-hailing services have become essential for people's daily commuting. Order dispatch is a critical problem in on-demand car-hailing services. However, in most existing works, the service provider is asked to set a unified pick-up distance to prevent long waiting time for requesters. Indeed, different requesters have different tolerance for pick-up distance, and some requesters may accept longer pick-ups if offered discounts for payment. Regarding this fact, we formulate discount-based order dispatch as a coupling of two subproblems, discount determination and order dispatch, aiming to dispatch more orders and thereby more platform profits. We propose customized methods to solve the problems for shared and non-shared mobility services, respectively. We also conduct extensive experiments to evaluate the effectiveness and efficiency of our proposed methods on a real dataset, which shows that our methods can achieve 170% improvements in non-shard services and 43% improvements in ridesharing services on average in terms of attained profit compared to the widely adopted baselines.

Web records are structured data on a Web page that embeds records retrieved from an underlying database according to some templates. Mining data records on the Web enables the integration of data from multiple Web sites for providing value-added services. Most existing works on Web record extraction make two key assumptions: (1) records are retrieved from databases with uniform schemas and (2) records are displayed in a linear structure on a Web page. These assumptions no longer hold on the modern Web. A Web page may present records of diverse entity types with different schemas and organize records hierarchically, in nested structures, to show richer relationships among records. In this paper, we revisit these assumptions and modify them to reflect Web pages on the modern Web. Based on the reformulated assumptions, we introduce the concept of invariant in Web data records and propose Miria ( Mi ning r ecord i nvari a nt), a bottom-up, recursive approach to construct the Web records from the invariants. The proposed approach is both effective and efficient, consistently outperforming the state-of-the-art Web record extraction methods on modern Web pages.