Location-based search engines tasks and capabilities: A comparative study

Location-based web searching is one of the popular tasks expected from the search engines. A location-based query consists of a topic and a reference location. Unlike general web search, in location-based search it is expected to find and rank documents which are not only related to the query topic but also geographically related to the location which the query is associated with. There are several issues for developing effective geographic search engines and so far, no global location-based search engine has been reported. Location ambiguity, lack of geographic information on web pages, language-based and country-dependent addressing styles, and multiple locations related to a single web resource are notable difficulties. Search engine companies have started to develop and offer location-based services. However, they are still geographically limited and have not become as successful and popular as general search engines. This paper reviews the architecture and tasks of location-based search engines and compares the capabilities, functionalities and coverage of the current geographic search engines with a user-oriented approach. Copyrigh

IDeixis : image-based deixis for recognizing locations

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.Includes bibliographical references (p. 31-32).In this thesis, we describe an approach to recognizing location from camera-equipped mobile devices using image-based web search. This is an image-based deixis capable of pointing at a distant location away from the user's current location. We demonstrate our approach on an application allowing users to browse web pages matching the image of a nearby location. Common image search metrics can match images captured with a camera-equipped mobile device to images found on the World Wide Web. The users can recognize the location if those pages contain information about this location (e.g. name, facts, stories ... etc). Since the amount of information displayable on the device is limited, automatic keyword extraction methods can be applied to help efficiently identify relevant pieces of location information. Searching the entire web can be computationally overwhelming, so we devise a hybrid image-and-keyword searching technique. First, image-search is performed over images and links to their source web pages in a database that indexes only a small fraction of the web. Then, relevant keywords on these web pages are automatically identified and submitted to an existing text-based search engine (e.g. Google) that indexes a much larger portion of the web. Finally, the resulting image set is filtered to retain images close to the original query in terms of visual similarity. It is thus possible to efficiently search hundreds of millions of images that are not only textually related but also visually relevant.by Pei-Hsiu Yeh.S.M

Ranked Spatial-keyword Search over Web-accessible Geotagged Data: State of the Art

Search engines, such as Google and Yahoo!, provide efficient retrieval and ranking of web pages based on queries consisting of a set of given keywords. Recent studies show that 20% of all Web queries also have location constraints, i.e., also refer to the location of a geotagged web page. An increasing number of applications support location based keyword search, including Google Maps, Bing Maps, Yahoo! Local, and Yelp. Such applications depict points of interest on the map and combine their location with the keywords provided by the associated document(s). The posed queries consist of two conditions: a set of keywords and a spatial location. The goal is to find points of interest with these keywords close to the location. We refer to such a query as spatial-keyword query. Moreover, mobile devices nowadays are enhanced with built-in GPS receivers, which permits applications (such as search engines or yellow page services) to acquire the location of the user implicitly, and provide location-based services. For instance, Google Mobile App provides a simple search service for smartphones where the location of the user is automatically captured and employed to retrieve results relevant to her current location. As an example, a search for ”pizza” results in a list of pizza restaurants nearby the user. Given the popularity of spatial-keyword queries and their wide applicability in practical scenarios, it is critical to (i) establish mechanisms for efficient processing of spatial-keyword queries, and (ii) support more expressive query formulation by means of novel 1 query types. Although studies on both keyword search and spatial queries do exist, the problem of combining the search capabilities of both simultaneously has received little attention

Location Selection Query in Google Maps using Voronoi-based Spatial Skyline (VS2) Algorithm

Google Maps is one of the popular location selection systems. One of the popular features of Google Maps is nearby search. For example, someone who wants to find the closest restaurants to his location can use the nearby search feature. This feature only considers one specific location in providing the desired place choice. In a real-world situation, there may be a need to consider more than one location in selecting the desired place. Assume someone would like to choose a hotel close to the conference hall, the museum, beach, and souvenir store. In this situation, nearby search feature in Google Maps may not be able to suggest a list of hotels that are interesting for him based on the distance from each destination places. In this paper, we have successfully developed a web-based application of Google Maps search using Voronoi-based Spatial Skyline (VS2) algorithm to choose some Point Of Interest (POI) from Google Maps as their considered locations to select desired place. We used Google Maps API to provide POI information for our web-based application. The experiment result showed that the execution time increases while the number of considered location increases

Virtual Location-Based Services: Merging the Physical and Virtual World

Location-based services gained much popularity through providing users with helpful information with respect to their current location. The search and recommendation of nearby locations or places, and the navigation to a specific location are some of the most prominent location-based services. As a recent trend, virtual location-based services consider webpages or sites associated with a location as 'virtual locations' that online users can visit in spite of not being physically present at the location. The presence of links between virtual locations and the corresponding physical locations (e.g., geo-location information of a restaurant linked to its website), allows for novel types of services and applications which constitute virtual location-based services (VLBS). The quality and potential benefits of such services largely depends on the existence of websites referring to physical locations. In this paper, we investigate the usefulness of linking virtual and physical locations. For this, we analyze the presence and distribution of virtual locations, i.e., websites referring to places, for two Irish cities. Using simulated tracks based on a user movement model, we investigate how mobile users move through the Web as virtual space. Our results show that virtual locations are omnipresent in urban areas, and that the situation that a user is close to even several such locations at any time is rather the normal case instead of the exception

An Application of Web 3.0: Positive WOM for Mobile Location-Based Apparel Shopping Services Usage

Web 3.0 is defined as the next paradigm shift of the Internet taking the best of web 2.0, including rich Internet applications and social media, and bringing them to mobile Internet devices and digital signage. Web 3.0 trends include a shift to outernet, location-based experiences, and the use of voice recognition in search applications (Buscemi & Marks, 2010). Mobile location-based services (LBS) offer shoppers reward opportunities when they physically visit stores or scan certain items

A Utility-Theoretic Approach to Privacy in Online Services

Online offerings such as web search, news portals, and e-commerce applications face the challenge of providing high-quality service to a large, heterogeneous user base. Recent efforts have highlighted the potential to improve performance by introducing methods to personalize services based on special knowledge about users and their context. For example, a user's demographics, location, and past search and browsing may be useful in enhancing the results offered in response to web search queries. However, reasonable concerns about privacy by both users, providers, and government agencies acting on behalf of citizens, may limit access by services to such information. We introduce and explore an economics of privacy in personalization, where people can opt to share personal information, in a standing or on-demand manner, in return for expected enhancements in the quality of an online service. We focus on the example of web search and formulate realistic objective functions for search efficacy and privacy. We demonstrate how we can find a provably near-optimal optimization of the utility-privacy tradeoff in an efficient manner. We evaluate our methodology on data drawn from a log of the search activity of volunteer participants. We separately assess users’ preferences about privacy and utility via a large-scale survey, aimed at eliciting preferences about peoples’ willingness to trade the sharing of personal data in returns for gains in search efficiency. We show that a significant level of personalization can be achieved using a relatively small amount of information about users

Predicting Evacuation Decisions using Representations of Individuals' Pre-Disaster Web Search Behavior

Predicting the evacuation decisions of individuals before the disaster strikes is crucial for planning first response strategies. In addition to the studies on post-disaster analysis of evacuation behavior, there are various works that attempt to predict the evacuation decisions beforehand. Most of these predictive methods, however, require real time location data for calibration, which are becoming much harder to obtain due to the rising privacy concerns. Meanwhile, web search queries of anonymous users have been collected by web companies. Although such data raise less privacy concerns, they have been under-utilized for various applications. In this study, we investigate whether web search data observed prior to the disaster can be used to predict the evacuation decisions. More specifically, we utilize a "session-based query encoder" that learns the representations of each user's web search behavior prior to evacuation. Our proposed approach is empirically tested using web search data collected from users affected by a major flood in Japan. Results are validated using location data collected from mobile phones of the same set of users as ground truth. We show that evacuation decisions can be accurately predicted (84%) using only the users' pre-disaster web search data as input. This study proposes an alternative method for evacuation prediction that does not require highly sensitive location data, which can assist local governments to prepare effective first response strategies.Comment: Accepted in ACM KDD 201

The Effect of Web Usability on Users’ Web Experience

The ease with which a website visitor can find what they need is positively correlated with visitor satisfaction(Institute for Dynamic Educational Advancement, 2008). Web usability is a field that studies what factors affect the visitor’s ability to navigate through a website. Although there are publications outlining specific usability guidelines, many of them have little or no academic research to support the claim. HHS developed a list of 209 guidelines and rated each according to their strength of evidence (research-based support, 5 – high, 1 – low). Using heuristic evaluation and usability testing, this study provides additional research-based knowledge for those guidelines rated with a low strength of evidence. Results indicate that users desire printer-friendly webpages, require feedback on their location within the website, find linking to related content helpful, and expect a search option to be provided on every page. Additional research is necessary to determine if providing descriptive page titles or labeling pushbuttons clearly is important to web usability