With hundreds of millions of users reporting locations and embracing mobile technologies, Location Based Services (LBSs) are raising new challenges. In this dissertation, we address three emerging problems in location services, where geolocation data plays a central role. First, to handle the unprecedented growth of generated geolocation data, existing location services rely on geospatial database systems. However, their inability to leverage combined geographical and textual information in analytical queries (e.g. spatial similarity joins) remains an open problem. To address this, we introduce SpsJoin, a framework for computing spatial set-similarity joins. SpsJoin handles combined similarity queries that involve textual and spatial constraints simultaneously. LBSs use this system to tackle different types of problems, such as deduplication, geolocation enhancement and record linkage. We define the spatial set-similarity join problem in a general case and propose an algorithm for its efficient computation. Our solution utilizes parallel computing with MapReduce to handle scalability issues in large geospatial databases. Second, applications that use geolocation data are seldom concerned with ensuring the privacy of participating users. To motivate participation and address privacy concerns, we propose iSafe, a privacy preserving algorithm for computing safety snapshots of co-located mobile devices as well as geosocial network users. iSafe combines geolocation data extracted from crime datasets and geosocial networks such as Yelp. In order to enhance iSafe's ability to compute safety recommendations, even when crime information is incomplete or sparse, we need to identify relationships between Yelp venues and crime indices at their locations. To achieve this, we use SpsJoin on two datasets (Yelp venues and geolocated businesses) to find venues that have not been reviewed and to further compute the crime indices of their locations. Our results show a statistically significant dependence between location crime indices and Yelp features. Third, review centered LBSs (e.g., Yelp) are increasingly becoming targets of malicious campaigns that aim to bias the public image of represented businesses. Although Yelp actively attempts to detect and filter fraudulent reviews, our experiments showed that Yelp is still vulnerable. Fraudulent LBS information also impacts the ability of iSafe to provide correct safety values. We take steps toward addressing this problem by proposing SpiDeR, an algorithm that takes advantage of the richness of information available in Yelp to detect abnormal review patterns. We propose a fake venue detection solution that applies SpsJoin on Yelp and U.S. housing datasets. We validate the proposed solutions using ground truth data extracted by our experiments and reviews filtered by Yelp.

本研究目的在於了解市面上英語教學雜誌中，如何再現文化相關的議題。其中，英語教學雜誌使用甚麼方式來再現不同文化和它們所呈現的內容為何為本研究的軸心。此研究採用質化的文本分析法細讀從2009年6月號到2010年5月號的兩本初級英語教學雜誌---"大家說英語"和"ABC互動英語雜誌"的文化內容。 研究發現兩本雜誌都使用描述性文章(descriptive text)和圖片來敘文化相關的議題，而呈現的文化內容多以節慶、旅遊、文學等主題為主；"大家說英語"著重在美國生活文化的介紹；而"ABC互動英文雜誌"則以本土化來結合異國文化。 / This study aims to seek what and how culture-related contents are represented and introduced in English learning materials. Two best-selling English learning magazines targeting at basic-level English learners are selected—“Let’s Talk in English” and “ABC Interactive English Magazine”. Through integrating and re-categorizing the classification of cultural themes developed by Fleewelling (1994), Pesola (1991), Robinson (1982), and Chen (2002), the study creates a new system to classify different culture-related topics. Combining with textual analysis, the study examines the forms used to show culture-related topics, the representation of different cultural themes, and the balance of introducing different cultures. Moreover, the similarities and differences in terms of the way both English learning magazines represent cultural themes are addressed. The result shows that informative text, contextualized practice, vocabulary, and pictures are forms commonly used by both magazines. In Let’s Talk in English (LTE), various forms are adopted in introducing the same topic; while ABC Interactive English Magazine (ABC) uses only one form on each topic. Both magazines include big C themes, i.e. politics, economy, and literature and small c themes such as celebration of holidays and traveling. However, LTE uses examples concerning American lifestyles to illustrate these themes, whereas ABC combines more different foreign and local cultures in representing culture-related topics. The findings also suggest the diversity and immediacy of English learning magazines on the representation of culture-related topics.