Spatio-textual indexing for geographical search on the web

Many web documents refer to specific geographic localities and many people include geographic context in queries to web search engines. Standard web search engines treat the geographical terms in the same way as other terms. This can result in failure to find relevant documents that refer to the place of interest using alternative related names, such as those of included or nearby places. This can be overcome by associating text indexing with spatial indexing methods that exploit geo-tagging procedures to categorise documents with respect to geographic space. We describe three methods for spatio-textual indexing based on multiple spatially indexed text indexes, attaching spatial indexes to the document occurrences of a text index, and merging text index access results with results of access to a spatial index of documents. These schemes are compared experimentally with a conventional text index search engine, using a collection of geo-tagged web documents, and are shown to be able to compete in speed and storage performance with pure text indexing

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

Automatic Geotagging of Russian Web Sites

The poster describes a fast, simple, yet accurate method to associate large amounts of web resources stored in a search engine database with geographic locations. The method uses location-by-IP data, domain names, and content-related features: ZIP and area codes. The novelty of the approach lies in building location-by-IP database by using continuous IP blocks method. Another contribution is domain name analysis. The method uses search engine infrastructure and makes it possible to effectively associate large amounts of search engine data with geography on a regular basis. Experiments ran on Yandex search engine index; evaluation has proved the efficacy of the approach.ACM Special Interest Group on Hypertext, Hypermedia, and We

Discovery of User-Generated Geographic Data Using Web Search Engines

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SEO - Search Engine Optimization

Tato bakalářská práce obsahuje přehled faktorů ovlivňujících viditelnost webu ve vyhledávačích včetně optimalizace pro geografické oblasti, různé jazykové modifikace apod. Dále v práci najdete krátký přehled nástrojů, které usnadňují optimalizaci. Hlavním cílem je návrh a implementace webové aplikace, která slouží pro analýzu webových stránek včetně sledování pozic ve vyhledávačích.This Bachelor's thesis presents an overview of factors affecting site visibility in search engines including optimization for geographic areas, various language modifications, etc. The Thesis gives a brief overview of tools that help in the process of web optimization. The main goal is to design and implement a web application capable of analyzing web pages and reporting positions in search engines.

Hierarchical Geographical Identifiers As An Indexing Technique For Geographic Information Retrieval

Location plays an ever increasing role in modern web-based applications. Many of these applications leverage off-the-shelf search engine technology to provide interactive access to large collections of data. Unfortunately, these commodity search engines do not provide special support for location-based indexing and retrieval. Many applications overcome this constraint by applying geographic bounding boxes in conjunction with range queries. We propose an alternative technique based on geographic identifiers and suggest it will yield faster query evaluation and provide higher search precision. Our experiment compared the two approaches by executing thousands of unique queries on a dataset with 1.8 million records. Based on the quantitative results obtained, our technique yielded drastic performance improvements in both query execution time and precision

Geographic Information System Design for Bridge Management in Brebes Regency

Purpose: geographic information system (GIS) design to monitoring and management of bridges that have geographic references, as well as a tool for planning activity programs (maintenance, rehabilitation, strengthening or replacement) of bridges.Design/methodology/approach: waterfallFindings/result: web-based geographic information system (GIS) for bridge management in Brebes RegencyOriginality/value/state of the art: this research does not only focus on site search as the main strength of GIS but maximizes bridge inspection activities as an important part of the bridge management system as a tool for planning bridge construction and maintenance activitie

Location-Aware Keyword Query Proposal Based On File Proximity

Web search query suggestions aid users in finding relevant content without requiring them to know how to search for it exactly. Existing keyword suggestion approaches do not take into account user locations and query results; i.e. the geographic proximity of a user to the results found is not taken as a consideration in the recommendation. However, the relevancy of search results is known to be connected to their geographic proximity to the query emitter in many applications (e.g. location-based services). We build a keyword query suggestion framework that is aware of location. We offer a weighted keyword-document graph capturing both the semitone significance between keyword searches and the geographic distance between the documents generated and the user location. To choose the highest-scoring keyword queries as suggestions, the graph is viewed in a random-walk-with-restart method. A partition-based technique that's up to an order of magnitude better than the baseline beats the baseline method. To assess the performance of our framework and algorithms, we use real data