Report of MIRACLE team for Geographical IR in CLEF 2006

The main objective of the designed experiments is testing the effects of geographical information retrieval from documents that contain geographical tags. In the designed experiments we try to isolate geographical retrieval from textual retrieval replacing all geo-entity textual references from topics with associated tags and splitting the retrieval process in two phases: textual retrieval from the textual part of the topic without geo-entity references and geographical retrieval from the tagged text generated by the topic tagger. Textual and geographical results are combined applying different techniques: union, intersection, difference, and external join based. Our geographic information retrieval system consists of a set of basics components organized in two categories: (i) linguistic tools oriented to textual analysis and retrieval and (ii) resources and tools oriented to geographical analysis. These tools are combined to carry out the different phases of the system: (i) documents and topics analysis, (ii) relevant documents retrieval and (iii) result combination. If we compare the results achieved to the last campaign’s results, we can assert that mean average precision gets worse when the textual geo-entity references are replaced with geographical tags. Part of this worsening is due to our experiments return cero pertinent documents if no documents satisfy de geographical sub-query. But if we only analyze the results of queries that satisfied both textual and geographical terms, we observe that the designed experiments recover pertinent documents quickly, improving R-Precision values. We conclude that the developed geographical information retrieval system is very sensible to textual georeference and therefore it is necessary to improve the name entity recognition module

MIRACLE at GeoCLEF Query Parsing 2007: Extraction and Classification of Geographical Information

This paper describes the participation of MIRACLE research consortium at the Query Parsing task of GeoCLEF 2007. Our system is composed of three main modules. First, the Named Geo-entity Identifier, whose objective is to perform the geo-entity identification and tagging, i.e., to extract the “where” component of the geographical query, should there be any. This module is based on a gazetteer built up from the Geonames geographical database and carries out a sequential process in three steps that consist on geo-entity recognition, geo-entity selection and query tagging. Then, the Query Analyzer parses this tagged query to identify the “what” and “geo-relation” components by means of a rule-based grammar. Finally, a two-level multiclassifier first decides whether the query is indeed a geographical query and, should it be positive, then determines the query type according to the type of information that the user is supposed to be looking for: map, yellow page or information. According to a strict evaluation criterion where a match should have all fields correct, our system reaches a precision value of 42.8% and a recall of 56.6% and our submission is ranked 1st out of 6 participants in the task. A detailed evaluation of the confusion matrixes reveal that some extra effort must be invested in “user-oriented” disambiguation techniques to improve the first level binary classifier for detecting geographical queries, as it is a key component to eliminate many false-positives

Contextual queries and situated information needs for mobile users

The users of mobile devices increasingly use networked services to address their information needs. Questions asked by mobile users are strongly influenced by contextual factors such as location, conversation and activity. We report on a diary study performed to better understand mobile information needs. Participants’ diary entries are used as a basis for discussing the geographical and situational context in which mobile information behaviour occurs. The suitability of user queries to be answered by a portable knowledge collection and web search are also considered. We find that the type of questions recorded by participants varies across their locations, with differences between home, shopping and in-car contexts. These variations occur both in the query terms and in the form of desired answers. Both the location of queries and the participants’ activities affected participants’ questions. When information needs were affected by both location and activity, they tended to be strongly affected by both factors. The overall picture that emerges is one of multiple contextual influences interacting to shape mobile information needs. Mobile devices that attempt to adapt to users’ context will need to account for a rich variety of situational factors

Contextual Media Retrieval Using Natural Language Queries

The widespread integration of cameras in hand-held and head-worn devices as well as the ability to share content online enables a large and diverse visual capture of the world that millions of users build up collectively every day. We envision these images as well as associated meta information, such as GPS coordinates and timestamps, to form a collective visual memory that can be queried while automatically taking the ever-changing context of mobile users into account. As a first step towards this vision, in this work we present Xplore-M-Ego: a novel media retrieval system that allows users to query a dynamic database of images and videos using spatio-temporal natural language queries. We evaluate our system using a new dataset of real user queries as well as through a usability study. One key finding is that there is a considerable amount of inter-user variability, for example in the resolution of spatial relations in natural language utterances. We show that our retrieval system can cope with this variability using personalisation through an online learning-based retrieval formulation.Comment: 8 pages, 9 figures, 1 tabl

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

Toward user oriented semantic geographical information systems

User Oriented Geographical Information Systems, a recent adaptation of classical GIS concepts to everyday usage, are becoming more and more present in the web landscape. Recent developments show the need of adding higher semantic levels to the existing frameworks, to improve their usage, as well as to ease scalability. We point out limits of actual examples, related to handling heterogeneous data, scalability issues, and expressiveness, and suggest a framework for building a Semantic User Oriented GIS. Notably this framework aims to address the peculiarities of the geographical space domain, and to offer a cognitively sound interface to the user

University of Twente at GeoCLEF 2006: geofiltered document retrieval

In this report we describe the approach of the University of Twente to the 2006 Geo-CLEF task. It is based on retrieval by content and the subsequent filtering by geographical relevance utilizing a gazetteer. The results do not show an improvement inretrieval performance when taking geographical information into account

Voronoi-Based Region Approximation for Geographical Information Retrieval with Gazetteers

Gazetteers and geographical thesauri can be regarded as parsimonious spatial models that associate geographical location with place names and encode some semantic relations between the names. They are of particular value in processing information retrieval requests in which the user employs place names to specify geographical context. Typically the geometric locational data in a gazetteer are confined to a simple footprint in the form of a centroid or a minimum bounding rectangle, both of which can be used to link to a map but are of limited value in determining spatial relationships. Here we describe a Voronoi diagram method for generating approximate regional extents from sets of centroids that are respectively inside and external to a region. The resulting approximations provide measures of areal extent and can be used to assist in answering geographical queries by evaluating spatial relationships such as distance, direction and common boundary length. Preliminary experimental evaluations of the method have been performed in the context of a semantic modelling system that combines the centroid data with hierarchical and adjacency relations between the associated place names

GeoCLEF 2007: the CLEF 2007 cross-language geographic information retrieval track overview

GeoCLEF ran as a regular track for the second time within the Cross Language Evaluation Forum (CLEF) 2007. The purpose of GeoCLEF is to test and evaluate cross-language geographic information retrieval (GIR): retrieval for topics with a geographic specification. GeoCLEF 2007 consisted of two sub tasks. A search task ran for the third time and a query classification task was organized for the first. For the GeoCLEF 2007 search task, twenty-five search topics were defined by the organizing groups for searching English, German, Portuguese and Spanish document collections. All topics were translated into English, Indonesian, Portuguese, Spanish and German. Several topics in 2007 were geographically challenging. Thirteen groups submitted 108 runs. The groups used a variety of approaches. For the classification task, a query log from a search engine was provided and the groups needed to identify the queries with a geographic scope and the geographic components within the local queries

Contextual queries express mobile information needs

The users of mobile devices increasingly use networked services to address their information needs. Questions asked by mobile users are strongly influenced by contextual factors such as location, conversation and activity. We report on a diary study performed to better understand mobile information needs. We find that the type of questions recorded by participants varies across their locations, with differences between home, shopping and in-car contexts. These variations occur both in the query terms and in the form of desired answers. Both the location of queries and the participants' activities affected participants' questions. When information needs were affected by both location and activity, they tended to be strongly affected by both factors. The overall picture that emerges is one of multiple contextual influences interacting to shape mobile information needs. Mobile devices that attempt to adapt to users' context will need to account for a rich variety of situational factors