{"title":"A ranking measure for top-k moving object trajectories search","authors":"Vikram Goyal, S. Navathe","doi":"10.1145/2533888.2533933","DOIUrl":"https://doi.org/10.1145/2533888.2533933","url":null,"abstract":"In this paper we present a new ranking measure for Top-k Trajectory query. A trajectory is defined as a sequence of places with each place having an associated text description with them. A top-k trajectory query consists of a set of locations and a set of activities, and returns a set of relevant trajectories to a user. A trajectory is considered more relevant if it has query activities at places nearby to the query locations. The proposed ranking measure helps to select highly relevant trajectories by capturing the correlation between trajectory places and activities while computing a trajectory relevance score. Previous works on Top-k trajectory query computed a trajectory relevance score either on the basis of spatial proximity or on the basis of combination of spatial proximity and textual similarity in some user defined proportion. These works did not consider association of spatial and textual dimensions, and hence may return trajectories that have query activities at trajectory places very far away from the query locations. In addition to the proposal of a ranking metric, we also give an algorithm to implement the proposed metric efficiently. Finally, we do an experimental study on a real dataset to demonstrate that the proposed ranking measure is indeed effective in terms of retrieval of trajectories that have query activities at places near to the query locations.","PeriodicalId":167948,"journal":{"name":"Workshop on Geographic Information Retrieval","volume":"334 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132822947","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}
Damien Palacio, G. Cabanac, G. Hubert, K. Pinel-Sauvagnat, C. Sallaberry
{"title":"Prototyping a personalized contextual retrieval framework","authors":"Damien Palacio, G. Cabanac, G. Hubert, K. Pinel-Sauvagnat, C. Sallaberry","doi":"10.1145/2533888.2533935","DOIUrl":"https://doi.org/10.1145/2533888.2533935","url":null,"abstract":"We introduce a framework for searching places according to user interests and spatial context. Our framework combines existing geo-tools or services (e.g., Google Places, Yahoo! BOSS Geo Services, PostGIS, Gisgraphy, Geonames) and ranks results according to features such as distance, popularity, and user preferences. We used this framework to participate in the TREC 2013 Contextual Suggestion Track.","PeriodicalId":167948,"journal":{"name":"Workshop on Geographic Information Retrieval","volume":"252 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133227161","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}
{"title":"Structured toponym resolution using combined hierarchical place categories","authors":"M. Adelfio, H. Samet","doi":"10.1145/2533888.2533931","DOIUrl":"https://doi.org/10.1145/2533888.2533931","url":null,"abstract":"Determining geographic interpretations for place names, or toponyms, involves resolving multiple types of ambiguity. Place names commonly occur within lists and data tables, whose authors frequently omit qualifications (such as city or state containers) for place names because they expect the meaning of individual place names to be obvious from context. We present a novel technique for place name disambiguation (also known as toponym resolution) that uses Bayesian inference to assign categories to lists or tables containing place names, and then interprets individual toponyms based on the most likely category assignments. The categories are defined as nodes in hierarchies along three orthogonal dimensions: place types (e.g., cities, capitals, rivers, etc.), geographic containers, and prominence (e.g., based on population).","PeriodicalId":167948,"journal":{"name":"Workshop on Geographic Information Retrieval","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114805003","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}
{"title":"Evidential location estimation for events detected in Twitter","authors":"Özer Özdikis, Halit Oğuztüzün, P. Senkul","doi":"10.1145/2533888.2533929","DOIUrl":"https://doi.org/10.1145/2533888.2533929","url":null,"abstract":"Event detection from microblogs and social networks, especially from Twitter, is an active and rich research topic. By grouping similar tweets in clusters, people can extract events and follow the happenings in a community. In this work, we focus on estimating the geographical locations of events that are detected in Twitter. An important novelty of our work is the application of evidential reasoning techniques, namely the Demspter-Shafer Theory (DST), for this problem. By utilizing several features of tweets, we aim to produce belief intervals for a set of possible discrete locations. DST helps us deal with uncertainties, assign belief values to subsets of solutions, and combine pieces of evidence obtained from different tweet features. The initial results on several real cases suggest the applicability and usefulness of DST for the problem.","PeriodicalId":167948,"journal":{"name":"Workshop on Geographic Information Retrieval","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134217866","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}
M. Karimzadeh, W. Huang, Siddhartha Banerjee, J. O. Wallgrün, F. Hardisty, Scott Pezanowski, P. Mitra, A. MacEachren
{"title":"GeoTxt: a web API to leverage place references in text","authors":"M. Karimzadeh, W. Huang, Siddhartha Banerjee, J. O. Wallgrün, F. Hardisty, Scott Pezanowski, P. Mitra, A. MacEachren","doi":"10.1145/2533888.2533942","DOIUrl":"https://doi.org/10.1145/2533888.2533942","url":null,"abstract":"Associating place name mentions in unstructured text with their actual references in geographic space is vital to enable spatial queries and analysis. In this paper, we introduce GeoTxt, a web API plus human-usable web tool designed and implemented to tackle three components of place-reference processing from text, namely: extraction, disambiguation, and geolocation of place names mentioned in unstructured text. Current GeoTxt development is focused particularly on support for processing short microblog posts.","PeriodicalId":167948,"journal":{"name":"Workshop on Geographic Information Retrieval","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134543984","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}
{"title":"Construction of a Japanese gazetteers for Japanese local toponym disambiguation","authors":"Masaharu Yoshioka, Takahiro Fujiwara","doi":"10.1145/2533888.2533930","DOIUrl":"https://doi.org/10.1145/2533888.2533930","url":null,"abstract":"When processing toponym information in natural language text, it is crucial to have a good gazetteers. There are several well-organized gazetteers for English text, but they do not cover Japanese local toponyms. In this paper, we introduce a Japanese gazetteers based on Open Data (e.g., the Toponym database distributed by Japanese ministries, Wikipedia, and GeoNames) and propose a toponym disambiguation framework that uses the constructed gazetteers. We also evaluate our approach based on a blog corpus that contains place names with high ambiguity.","PeriodicalId":167948,"journal":{"name":"Workshop on Geographic Information Retrieval","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121081617","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}
{"title":"Extraction and exploration of spatio-temporal information in documents","authors":"Jannik Strotgen, Michael Gertz, Pavel Popov","doi":"10.1145/1722080.1722101","DOIUrl":"https://doi.org/10.1145/1722080.1722101","url":null,"abstract":"In the past couple of years, there have been significant advances in the areas of temporal information retrieval (TIR) and geographic information retrieval (GIR), each focusing on extracting and utilizing temporal and geographic information, respectively, from documents for search and exploration tasks. Interestingly, there is only little work that combines models, techniques and applications from these two areas to support scenarios and applications where temporal and geographic information in combination provide interesting meaningful nuggets in document exploration tasks, such as visualizing a chronological sequence of events with their locations.\u0000 In this paper, we present an approach that combines the two areas of TIR and GIR. Using temporal and geographic information extracted from documents and recorded in temporal and geographic document profiles, we show how co-occurrences of such information are determined and spatio-temporal document profiles are computed. Such profiles then provide the basis for a variety of document search and exploration tasks, such as visualizing the sequences of events on a map. We present a prototypical implementation of our system and demonstrate the effectiveness of combining GIR and TIR in the context of document exploration tasks.","PeriodicalId":167948,"journal":{"name":"Workshop on Geographic Information Retrieval","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133024411","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}
{"title":"Retrieving address-based locations from the web","authors":"Dirk Ahlers, Susanne CJ Boll","doi":"10.1145/1460007.1460015","DOIUrl":"https://doi.org/10.1145/1460007.1460015","url":null,"abstract":"Geospatial search for the Web determines the relation of documents' contents to a location within a region. For some pedestrian scenarios, information at a higher granularity down to individual buildings is necessary. In this paper, we describe a process for the extraction and simultaneous verification of precise addresses on German Web pages by a validating parser. We describe how an address-level location extraction can be aided by an extensive use of previous geographic knowledge and the use of its structure. The analysis of address structure, components and dependencies leads to the design of a geoparser that determines valid addresses within unstructured Web content. We further discuss some noteworthy issues that arise within the process.","PeriodicalId":167948,"journal":{"name":"Workshop on Geographic Information Retrieval","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126684375","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}
{"title":"Experiences in crawling deep web in the context of local search","authors":"Dheerendranath Mundluru, Xiongwu Xia","doi":"10.1145/1460007.1460016","DOIUrl":"https://doi.org/10.1145/1460007.1460016","url":null,"abstract":"Local search engines allow geographically constrained searching of businesses and their products or services. Some of the local search engines use crawlers for indexing Web page contents. These crawlers mostly index Web pages that are accessible through hyperlinks and which include desirable location information. It is extremely important for local search engines to also crawl additional high-quality \"local\" content (e.g., user reviews) that is available in the Deep Web. Much of this content is hidden behind search forms and is in the form of structured data, which is increasing very rapidly. In this paper, we present our experiences in crawling and extracting a wide variety of local structured data from large number of Deep Web resources. We discuss the challenges in crawling such sources and based on our experience we offer some effective principles to address them. Our experimental results on several Deep Web sources with local content show that the techniques discussed are highly effective.","PeriodicalId":167948,"journal":{"name":"Workshop on Geographic Information Retrieval","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117310887","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}
{"title":"Document retrieval using fuzzy related geographic ontologies","authors":"Maria Angelica A. Leite, I. Ricarte","doi":"10.1145/1460007.1460021","DOIUrl":"https://doi.org/10.1145/1460007.1460021","url":null,"abstract":"Many documents stored in digital libraries and document database include geographic references within their texts typically by means of place names. These geographic references can be associated to knowledge to help improve related retrieved documents. For example, in a meteorological document collection the climate knowledge can be associated to the geographic references allowing the retrieval of relevant climate or geographic related documents to an initial user query. In order to explore these issues this work describes a framework to encode a geographic knowledge base composed of multiple related ontologies whose relationships are expressed as fuzzy relations. Each ontology represents a distinct area of the knowledge domain related to geographic references. This knowledge organization is used in a fuzzy method to expand the user initial query. Each ontology can be represented independently as well as their relationships. The fuzzy query expansion method is tested with the Apache Lucene search engine improving the precision measure.","PeriodicalId":167948,"journal":{"name":"Workshop on Geographic Information Retrieval","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127942938","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}
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
