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 discovering co-located queries, which are geographic search requests for nearby search-locations. One example co-located query pattern is {"shopping mall", "parking"}. This pattern indicates that people often search "shopping mall" and "parking" over locations close to one another. Co-located queries have many applications, such as query suggestion, location recommendation, and local advertisement. We formally define 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 local and global. Experimental results show that the lattice based approach outperforms the basic approach in the number of patterns, the quality of patterns, and the proportion of local patterns.
{"title":"Discovering co-located queries in geographic search logs","authors":"Xiangye Xiao, Longhao Wang, Xing Xie, Qiong Luo","doi":"10.1145/1367798.1367812","DOIUrl":"https://doi.org/10.1145/1367798.1367812","url":null,"abstract":"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 discovering co-located queries, which are geographic search requests for nearby search-locations. One example co-located query pattern is {\"shopping mall\", \"parking\"}. This pattern indicates that people often search \"shopping mall\" and \"parking\" over locations close to one another. Co-located queries have many applications, such as query suggestion, location recommendation, and local advertisement. We formally define 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 local and global. Experimental results show that the lattice based approach outperforms the basic approach in the number of patterns, the quality of patterns, and the proportion of local patterns.","PeriodicalId":320466,"journal":{"name":"International Workshop on Location and the Web","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115056578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As the Internet continues to play an important role in many business applications, it becomes vital to increase the competitive edge by offering geographically tailored contents that reflect the common interests of the geographical region of the web visitors. In this paper, we define the problem of mining geographical-specific interests patterns. We utilize the quadtree to model the influence distributions of different features, and design an algorithm called Flex-iPROBER to mine geographical-specific interests patterns that are significant in a local region. We further examine how these patterns can change over time and develop an algorithm called MineGIC to efficiently discover pattern changes. Experiment results demonstrate that the proposed algorithms are scalable and efficient. Patterns discovered from real world web click datasets reveal interesting patterns and show the evolution of the interests of people in those regions.
{"title":"Discovering geographical-specific interests from web click data","authors":"Chang Sheng, W. Hsu, M. Lee","doi":"10.1145/1367798.1367805","DOIUrl":"https://doi.org/10.1145/1367798.1367805","url":null,"abstract":"As the Internet continues to play an important role in many business applications, it becomes vital to increase the competitive edge by offering geographically tailored contents that reflect the common interests of the geographical region of the web visitors. In this paper, we define the problem of mining geographical-specific interests patterns. We utilize the quadtree to model the influence distributions of different features, and design an algorithm called Flex-iPROBER to mine geographical-specific interests patterns that are significant in a local region. We further examine how these patterns can change over time and develop an algorithm called MineGIC to efficiently discover pattern changes. Experiment results demonstrate that the proposed algorithms are scalable and efficient. Patterns discovered from real world web click datasets reveal interesting patterns and show the evolution of the interests of people in those regions.","PeriodicalId":320466,"journal":{"name":"International Workshop on Location and the Web","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122466153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The web has become an important medium for news delivery and consumption. Fresh content about a variety of topics, events, and places is constantly being created and published on the web by news agencies around the world. As intuitively understood by readers, and studied in journalism, news articles produced by different social groups present different attitudes towards and interpretations of the same news issues. In this paper, we propose a new paradigm for aggregating news articles according to the local news sources associated with the stakeholders of the news issues. This new paradigm provides users the capability to aggregate and browse various local points of view about the news issues in which they are interested. We implement this paradigm in a system called LocalSavvy. LocalSavvy analyzes the news articles provided by users, using knowledge about locations automatically acquired from the web. Based on the analysis of the news issue, the system finds and aggregates local news articles published by official and unofficial news sources associated with the stakeholders. Moreover, opinions from those local social groups are extracted from the retrieved results, presented in the summaries and highlighted in the news web pages. We evaluate LocalSavvy with a user study. The quantitative and qualitative analysis shows that news articles aggregated by LocalSavvy present relevant and distinct local opinions, which can be clearly perceived by the subjects.
{"title":"LocalSavvy: aggregating local points of view about news issues","authors":"Jiahui Liu, L. Birnbaum","doi":"10.1145/1367798.1367804","DOIUrl":"https://doi.org/10.1145/1367798.1367804","url":null,"abstract":"The web has become an important medium for news delivery and consumption. Fresh content about a variety of topics, events, and places is constantly being created and published on the web by news agencies around the world. As intuitively understood by readers, and studied in journalism, news articles produced by different social groups present different attitudes towards and interpretations of the same news issues. In this paper, we propose a new paradigm for aggregating news articles according to the local news sources associated with the stakeholders of the news issues. This new paradigm provides users the capability to aggregate and browse various local points of view about the news issues in which they are interested. We implement this paradigm in a system called LocalSavvy. LocalSavvy analyzes the news articles provided by users, using knowledge about locations automatically acquired from the web. Based on the analysis of the news issue, the system finds and aggregates local news articles published by official and unofficial news sources associated with the stakeholders. Moreover, opinions from those local social groups are extracted from the retrieved results, presented in the summaries and highlighted in the news web pages. We evaluate LocalSavvy with a user study. The quantitative and qualitative analysis shows that news articles aggregated by LocalSavvy present relevant and distinct local opinions, which can be clearly perceived by the subjects.","PeriodicalId":320466,"journal":{"name":"International Workshop on Location and the Web","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126525798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The concept of location has become very popular in many applications on the Web, in particular for those which aim at connecting the real world with resources on the Web. However, the Web as it is today has no overall location concept, which means that applications have to introduce their own location concepts and have done so in incompatible ways. By turning the Web into a location-aware Web, which we call the "Locative Web", location-oriented applications get better support for their location concepts on the Web, and the Web becomes an information system where location-related information can be more easily shared across different applications and application areas. We describe a location concept for the Web supporting different location types, its embedding into some of the Web's core technologies, and prototype implementations of these concepts in location-enabled Web components.
{"title":"The locative web","authors":"Erik Wilde, M. Kofahl","doi":"10.1145/1367798.1367800","DOIUrl":"https://doi.org/10.1145/1367798.1367800","url":null,"abstract":"The concept of location has become very popular in many applications on the Web, in particular for those which aim at connecting the real world with resources on the Web. However, the Web as it is today has no overall location concept, which means that applications have to introduce their own location concepts and have done so in incompatible ways. By turning the Web into a location-aware Web, which we call the \"Locative Web\", location-oriented applications get better support for their location concepts on the Web, and the Web becomes an information system where location-related information can be more easily shared across different applications and application areas. We describe a location concept for the Web supporting different location types, its embedding into some of the Web's core technologies, and prototype implementations of these concepts in location-enabled Web components.","PeriodicalId":320466,"journal":{"name":"International Workshop on Location and the Web","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122027777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In typical concept@location-queries, the location is sometimes given by terms that cannot be found in gazetteers or geographic databases. Such terms usually describe vague geographical regions, but might also include more general terms like mining or theme parks, in which case the corresponding geographic footprint is less obvious. In the present paper we describe our approach to deal with such vague location specifications in geographic queries. Roughly, we determine a geographic representation for these location specifications from toponyms found in the top documents resulting from a query using the terms describing the location. In this paper we describe an efficient process to derive the geographic representation for such situations at query time. Furthermore, we present experiments depicting the performance of our approach as well as the result quality. Our approach allows for an efficient execution of queries such as camping ground near theme park. It can also be used as a standalone-application giving a visual impression of the geographic footprint of arbitrary terms.
{"title":"Determining geographic representations for arbitrary concepts at query time","authors":"A. Henrich, Volker Lüdecke","doi":"10.1145/1367798.1367802","DOIUrl":"https://doi.org/10.1145/1367798.1367802","url":null,"abstract":"In typical concept@location-queries, the location is sometimes given by terms that cannot be found in gazetteers or geographic databases. Such terms usually describe vague geographical regions, but might also include more general terms like mining or theme parks, in which case the corresponding geographic footprint is less obvious. In the present paper we describe our approach to deal with such vague location specifications in geographic queries. Roughly, we determine a geographic representation for these location specifications from toponyms found in the top documents resulting from a query using the terms describing the location.\u0000 In this paper we describe an efficient process to derive the geographic representation for such situations at query time. Furthermore, we present experiments depicting the performance of our approach as well as the result quality.\u0000 Our approach allows for an efficient execution of queries such as camping ground near theme park. It can also be used as a standalone-application giving a visual impression of the geographic footprint of arbitrary terms.","PeriodicalId":320466,"journal":{"name":"International Workshop on Location and the Web","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132453383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Florian A. Twaroch, Christopher B. Jones, A. Abdelmoty
Vernacular place names are names that are commonly in use to refer to geographical places. For purposes of effective information retrieval, the spatial extent associated with these names should be able to reflect people's perception of the place, even though this may differ sometimes from the administrative definition of the same place name. Due to their informal nature, vernacular place names are hard to capture, but methods to acquire and define vernacular place names are of great benefit to search engines and all kind of information services that deal with geographic data. This paper discusses the acquisition of vernacular use of place names from web sources and their representation as surface models derived by kernel density estimators.
{"title":"Acquisition of a vernacular gazetteer from web sources","authors":"Florian A. Twaroch, Christopher B. Jones, A. Abdelmoty","doi":"10.1145/1367798.1367808","DOIUrl":"https://doi.org/10.1145/1367798.1367808","url":null,"abstract":"Vernacular place names are names that are commonly in use to refer to geographical places. For purposes of effective information retrieval, the spatial extent associated with these names should be able to reflect people's perception of the place, even though this may differ sometimes from the administrative definition of the same place name. Due to their informal nature, vernacular place names are hard to capture, but methods to acquire and define vernacular place names are of great benefit to search engines and all kind of information services that deal with geographic data. This paper discusses the acquisition of vernacular use of place names from web sources and their representation as surface models derived by kernel density estimators.","PeriodicalId":320466,"journal":{"name":"International Workshop on Location and the Web","volume":"35 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114111796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Qingqing Gan, Josh Attenberg, Alexander Markowetz, Torsten Suel
Geography is becoming increasingly important in web search. Search engines can often return better results to users by analyzing features such as user location or geographic terms in web pages and user queries. This is also of great commercial value as it enables location specific advertising and improved search for local businesses. As a result, major search companies have invested significant resources into geographic search technologies, also often called local search. This paper studies geographic search queries, i.e., text queries such as "hotel new york" that employ geographical terms in an attempt to restrict results to a particular region or location. Our main motivation is to identify opportunities for improving geographical search and related technologies, and we perform an analysis of 36 million queries of the recently released AOL query trace. First, we identify typical properties of geographic search (geo) queries based on a manual examination of several thousand queries. Based on these observations, we build a classifier that separates the trace into geo and non-geo queries. We then investigate the properties of geo queries in more detail, and relate them to web sites and users associated with such queries. We also propose a new taxonomy for geographic search queries.
地理位置在网络搜索中变得越来越重要。搜索引擎通常可以通过分析网页中的用户位置或地理术语以及用户查询等特征,为用户返回更好的结果。这也具有很大的商业价值,因为它可以实现特定位置的广告,并改进对当地企业的搜索。因此,各大搜索公司在地理搜索技术上投入了大量资源,通常也被称为本地搜索。本文研究地理搜索查询,即使用地理术语试图将结果限制在特定区域或位置的文本查询,如“hotel new york”。我们的主要动机是确定改进地理搜索和相关技术的机会,我们对最近发布的AOL查询跟踪的3600万个查询进行了分析。首先,我们基于对数千个查询的人工检查确定地理搜索(geo)查询的典型属性。基于这些观察,我们构建了一个分类器,将跟踪分为地理查询和非地理查询。然后,我们更详细地研究地理查询的属性,并将它们与与此类查询相关的网站和用户联系起来。我们还提出了一种新的地理搜索查询分类法。
{"title":"Analysis of geographic queries in a search engine log","authors":"Qingqing Gan, Josh Attenberg, Alexander Markowetz, Torsten Suel","doi":"10.1145/1367798.1367806","DOIUrl":"https://doi.org/10.1145/1367798.1367806","url":null,"abstract":"Geography is becoming increasingly important in web search. Search engines can often return better results to users by analyzing features such as user location or geographic terms in web pages and user queries. This is also of great commercial value as it enables location specific advertising and improved search for local businesses. As a result, major search companies have invested significant resources into geographic search technologies, also often called local search.\u0000 This paper studies geographic search queries, i.e., text queries such as \"hotel new york\" that employ geographical terms in an attempt to restrict results to a particular region or location. Our main motivation is to identify opportunities for improving geographical search and related technologies, and we perform an analysis of 36 million queries of the recently released AOL query trace. First, we identify typical properties of geographic search (geo) queries based on a manual examination of several thousand queries. Based on these observations, we build a classifier that separates the trace into geo and non-geo queries. We then investigate the properties of geo queries in more detail, and relate them to web sites and users associated with such queries. We also propose a new taxonomy for geographic search queries.","PeriodicalId":320466,"journal":{"name":"International Workshop on Location and the Web","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116648028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents the IDIOM Media Watch on Climate Change (www.ecoresearch.net/climate), a prototypical implementation of an environmental portal that emphasizes the importance of location data for advanced Web applications. The introductory section outlines the process of retrofitting existing knowledge repositories with geographical context information, a process also referred to as geotagging. The paper then describes the portal's functionality, which aggregates, annotates and visualizes environmental articles from 150 Anglo-American news media sites. From 300,000 news media articles gathered in weekly intervals, the system selects about 10,000 focusing on environmental issues. The crawled data is indexed and stored in a central repository. Geographic location represents a central aspect of the application, but not the only dimension used to organize and filter content. Applying the concepts of location and topography to semantic similarity, the paper concludes with discussing information landscapes as alternative interface metaphor for accessing large Web repositories.
{"title":"Annotating and visualizing location data in geospatial web applications","authors":"A. Scharl, Hermann Stern, A. Weichselbraun","doi":"10.1145/1367798.1367809","DOIUrl":"https://doi.org/10.1145/1367798.1367809","url":null,"abstract":"This paper presents the IDIOM Media Watch on Climate Change (www.ecoresearch.net/climate), a prototypical implementation of an environmental portal that emphasizes the importance of location data for advanced Web applications. The introductory section outlines the process of retrofitting existing knowledge repositories with geographical context information, a process also referred to as geotagging. The paper then describes the portal's functionality, which aggregates, annotates and visualizes environmental articles from 150 Anglo-American news media sites. From 300,000 news media articles gathered in weekly intervals, the system selects about 10,000 focusing on environmental issues. The crawled data is indexed and stored in a central repository. Geographic location represents a central aspect of the application, but not the only dimension used to organize and filter content. Applying the concepts of location and topography to semantic similarity, the paper concludes with discussing information landscapes as alternative interface metaphor for accessing large Web repositories.","PeriodicalId":320466,"journal":{"name":"International Workshop on Location and the Web","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122071364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
For extracting the characteristics a specific geographic entity, and notably a place, we propose to use dynamic Extreme Tagging Systems in combination with the classic approach of static KR models like ontologies, thesauri and gazetteers. Indeed, we argue that in local search, the what that is queried is implicitly about places. However existing knowledge representation (KR) models, such as ontologies based on logical theories, conceptual spaces, affordance or other, cannot capture in isolation all aspects of the meaning of a place. Therefore we propose to use a combination of them based on the underlying notion of differences, linked elements of meaning without commitment to any KR model. Mapping to elements of different KR models can be made later to follow the requirements of a given task, supported by a KR representation of the elements that support this task. We show the usefulness of the approach for local search by applying it to the notion of place defined as a location that supports a homogeneous affordance field, i.e. the spatial area which allows me the do a particular thing, while allowing the homogeneity of movement, meaning that the previous field is not interrupted by any boundaries.
{"title":"A differential notion of place for local search","authors":"Vlad Tanasescu, J. Domingue","doi":"10.1145/1367798.1367801","DOIUrl":"https://doi.org/10.1145/1367798.1367801","url":null,"abstract":"For extracting the characteristics a specific geographic entity, and notably a place, we propose to use dynamic Extreme Tagging Systems in combination with the classic approach of static KR models like ontologies, thesauri and gazetteers. Indeed, we argue that in local search, the what that is queried is implicitly about places. However existing knowledge representation (KR) models, such as ontologies based on logical theories, conceptual spaces, affordance or other, cannot capture in isolation all aspects of the meaning of a place. Therefore we propose to use a combination of them based on the underlying notion of differences, linked elements of meaning without commitment to any KR model. Mapping to elements of different KR models can be made later to follow the requirements of a given task, supported by a KR representation of the elements that support this task. We show the usefulness of the approach for local search by applying it to the notion of place defined as a location that supports a homogeneous affordance field, i.e. the spatial area which allows me the do a particular thing, while allowing the homogeneity of movement, meaning that the previous field is not interrupted by any boundaries.","PeriodicalId":320466,"journal":{"name":"International Workshop on Location and the Web","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129320994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Local search is increasingly becoming a major focus point of research interest. It is a widely-recognized speciality search with a large application area. Its data is usually aggregated from a variety of sources. One as yet largely untapped source of location data is the WWW. Today, the Web does not explicitly reveal its location-relation; rather this information is hidden somewhere within pages' contents. To exploit such location information, we need to find, extract and geo-spatially index relevant Web pages. For an effective retrieval of such content, this paper examines the application of focused Web crawling to the geospatial domain. We describe our approach for a geo-aware focused crawling of urban areas and other regions with a high building density. We present our experimental results that give us insight into spatial Web information such as location density and link distance between topical pages. Our crawls and evaluations back our hypothesis that geospatially focused crawling is suitable for the urban geospatial topic.
{"title":"Urban web crawling","authors":"Dirk Ahlers, Susanne CJ Boll","doi":"10.1145/1367798.1367803","DOIUrl":"https://doi.org/10.1145/1367798.1367803","url":null,"abstract":"Local search is increasingly becoming a major focus point of research interest. It is a widely-recognized speciality search with a large application area. Its data is usually aggregated from a variety of sources. One as yet largely untapped source of location data is the WWW. Today, the Web does not explicitly reveal its location-relation; rather this information is hidden somewhere within pages' contents. To exploit such location information, we need to find, extract and geo-spatially index relevant Web pages. For an effective retrieval of such content, this paper examines the application of focused Web crawling to the geospatial domain. We describe our approach for a geo-aware focused crawling of urban areas and other regions with a high building density. We present our experimental results that give us insight into spatial Web information such as location density and link distance between topical pages. Our crawls and evaluations back our hypothesis that geospatially focused crawling is suitable for the urban geospatial topic.","PeriodicalId":320466,"journal":{"name":"International Workshop on Location and the Web","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129642637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}