Fig 1 - uploaded by Saeid Asadi
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An example of distribution of a Web resource users in different geographical locations (Here within the states of Australia)
Source publication
A location-based search engine must be able to find and assign proper locations to Web resources. Host, content and metadata location information are not sufficient to describe the location of resources as they are ambiguous or unavailable for many documents. We introduce target location as the location of users of Web resources. Target location is...
Context in source publication
Context 1
... that most of the people who use this site be from Toowong or areas around it. As the target locations of many resources are not determined explicitly, a reverse approach can be used to find this information. Suppose that 1000 people have visited webpage w and most of them are from Queensland. Queensland is then a possible target location of w ( Fig. ...
Citations
... A Geographical Information Retrieval System (GIRS) answers queries related to geographical locations. This kind of system is composed of four main tasks: geo-referencing, geo-scoping, indexing, and ranking (McCurley 2001, Watters and Amoudi 2002, Amitay et al. 2004, Wang et al. 2005, Asadi et al. 2006, Zhang et al. 2006. In this context, geo-referencing and geo-scoping are of particular interest as these are the grounds for indexing and ranking documents with respect to a user query. ...
Geo-referencing is a key task for geographical information retrieval because it allows unstructured or textual documents (i.e., Web pages) to be associated with geographical locations, which are then used by geo-search engines to index documents and search information by spatial criteria. This work proposes a strategy to extract geo-references from textual documents that combine natural language-processing techniques and co-reference solving heuristics, which in turn can be used to expand a geographical gazetteer. Implicit geographical entities (i.e., those entities referred to by pronouns) are recognized and incorporated into the gazetteer that is updated and used for geo-referencing tasks. Experiments show the promise of the approach to geo-referencing Web pages when dealing with implicit and/or indirect geo-references.
... Only pages with many back links have been regarded for the experiments [11]. Target location or the location of the visitors of a Web resource [3] has the same characteristics and advantages as geographical scope and can be applied to any Web resources which have some visitors even if they do not have any back links. However, this method also requires access to the Web site log files that are often inaccessible to search engines. ...
Search engines retrieve and rank Web pages which are not only relevant to a query but also important or popular for the users.
This popularity has been studied by analysis of the links between Web resources. Link-based page ranking models such as PageRank
and HITS assign a global weight to each page regardless of its location. This popularity measurement has shown successful
on general search engines. However unlike general search engines, location-based search engines should retrieve and rank higher
the pages which are more popular locally. The best results for a location-based query are those which are not only relevant
to the topic but also popular with or cited by local users. Current ranking models are often less effective for these queries
since they are unable to estimate the local popularity. We offer a model for calculating the local popularity of Web resources
using back link locations. Our model automatically assigns correct locations to the links and content and uses them to calculate
new geo-rank scores for each page. The experiments show more accurate geo-ranking of search engine results when this model
is used for processing location-based queries.
... Our work is related to query log mining that has been used to understand user behaviors on the Web and improve Web search [6, 7, 13]. Geographic aspect of query log has been analyzed in some recent work [14, 15, 11]. In this paper, we add a spatial dimension to query log mining. ...
A geographic search request contains a query consisting of one or more keywords, and a search-location that the user searches for. In this paper, we study the problem of discover- ing co-located queries, which are geographic search requests for nearby search-locations. One example co-located query pattern is {"shopping mall", "parking"}. This pattern indi- cates that people often search "shopping mall" and "park- ing" over locations close to one another. Co-located queries have many applications, such as query suggestion, location recommendation, and local advertisement. We formally de- fine co-located query patterns and propose two approaches to mining the patterns. Our basic approach is based on an existing spatial mining algorithm. To find more specific co-located queries that only appear in specific regions, we propose a lattice based approach. It divides the geographic space into regions and mines patterns in each region. We also define a locality measure to categorize patterns into lo- cal and global. Experimental results show that the lattice based approach outperforms the basic approach in the num- ber of patterns, the quality of patterns, and the proportion of local patterns.
... We also see interesting work on extending a location relation present on a page to a more thorough understanding of the page's geographical context. These approaches include the definition of a target audience, an actual audience [4], relationship to similar pages, geographical footprint [8] etc. The semantics of a location on a page can thus be manifold. ...
The Web today is considered to be a sheer unlimited re- source of interlinked information which can be explored fol- lowing links or can be found employing keyword-based search engines. A feature that becomes more and more relevant for our search and use of the Web is the geospatial reference of information. In this paper, we understand the Web as a vast geospatial information space in which most of the lo- cation information is still hidden inside the Web's content. We discuss the processes of uncovering hidden spatial infor- mation on the Web to realize a multitude of geospatial user scenarios. To explore the spatial character of the Web, lo- cation information needs to be discovered, understood, and augmented. By providing location insights into the existing Web, its content becomes accessible to spatial applications and thus allow users exploring the geospatial Web.
Full paper: http://journal.webscience.org/37/1/WebEvolve2008-06.pdf
... Geographic scope (Ding, Gravano & Shivakumar, 2000) is the geographic area that most of the back links on a page come from or refer to. Target location (Asadi et al, 2006) instead, considers the location of the visitors or the people who use a Web resource. Both Geographic Scope and Geographic Target are content-independent. ...
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.
Purpose – The purpose of this paper is to provide a conceptual model as a tool for Geographic Information Retrieval (GIR). Furthermore, the paper seeks to Identify and introduce current approaches on GIR, as well as, provides a lens to study GIR field.
Design/methodology/approach – Through a library-based study and a systematic literature review the conceptual model drawn from GIR literature.
Findings – Approaches on GIR could be divided into three categories, included, pattern-based models, ontology-based models, and machine learning models. The most of the GIR methods need for a gazetteer database or a geographic knowledge base to work properly. Although, interface and result ranking are crucial parts a GIR system that should be considered at the design step.
Originality/value – This paper is one of the first studies to seek a general review on GIR. Furthermore, the provided conceptual model is another value of this paper. As well as, the typology introduced by the paper assists researchers by providing a tool for systematic analysis of GIR.
Practical implications – Using the provided conceptual model, a GIR system – such as a search engine – could be designed.
Extraction of addresses and location names from Web pages is a challenging task for search engines. Traditional information
extraction and natural processing models remain unsuccessful in the context of the Web because of the uncontrolled heterogenous
nature of the Web resources as well as the effects of HTML and other markup tags. We describe a new pattern-based approach
for extraction of addresses from Web pages. Both HTML and vision-based segmentations are used to increase the quality of address
extraction. The proposed system uses several address patterns and a small table of geographic knowledge to hit addresses and
then itemize them into smaller components. The experiments show that this model can extract and itemize different addresses
effectively without large gazetteers or human supervision.
This paper introduces a new map browser of location based contents (LBC) that summarizes area characteristics. Recently various
web map services have been widely used to search web contents. As LBC increase, browsing a number of LBC which are viewed
as POI (point of interest) on a geographical map becomes inefficient. We tackle this issue by using AOI (area of interest)
instead of POI. With the AOI a user can instantly find area characteristics without viewing each content of POI. We assume
that semantically homogeneous and geographically distinguishable areas are suitable for the AOI. The AOI is formed by geo-semantic
clustering which is a co-clustering that takes into account both geographical and semantic aspects of POI information. By
the experiment using real LBC on the web, we confirmed our method has potential to extract good AOI.
This paper introduces BEIRA, an area-based map user interface for location-based contents. Recently, various web map services
are widely used to search for location-based contents. However, browsing a large number of contents that are arranged on a
map as points may be troublesome. We tackle this issue by using area-based representations instead of points. AOI (Area of
Interest), which is core concept of BEIRA, is an arbitrary shaped area boundary with text summary information. With AOI, users
can instantly grasp area characteristics without examining each point. AOI is deduced by performing geo-semantic co-clustering
of location-based contents. Geo-semantic co-clustering takes both geographic and semantic features of contents into account.
We confirm that the ratio of the geo-semantic blend is the key to deducing an appropriate boundary. We further propose and
evaluate location-aware term weighting to obtain an informative summary.
In this paper, we present a semantic model to represent spatiotemporal information for Web pages. Most Web pages in the real world are related to time and locations, thus our purpose is to enhance the traditional search engines with the ability of expressing spatiotemporal predictive. For this purpose, we need to extract the spatiotemporal information of Web pages into a formal representation structure. This paper aims at the representation of spatiotemporal information of Web pages. We will first study the spatiotemporal semantics of Web pages, and then construct a spatiotemporal semantic model for Web pages to represent the spatiotemporal semantics.
