XQL and proximal nodes

Baeza-Yates, Ricardo; Navarro, Gonzalo

doi:10.1002/asi.10061

Cited by 24 publications

(21 citation statements)

References 15 publications

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“…For retrieval, we have chosen to implement through XQuery [25], [26], [27], currently the most recent XML query language, and most powerful one compared to the older ones [28], [29].…”

Section: Discussionmentioning

confidence: 99%

Very high spatial resolution images: Segmenting, modeling and knowledge discovery

Lopez-Ornelas

2009

2009 17th International Conference on Geoinformatics

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In this paper we describe the basic functionalities of a system dedicated to process high-resolution satellite images and to handle them through (semi-) structured descriptors. These descriptors enable to manage in a unified representation two families of features extracted from the objects identified by image segmentation: the attributes characterizing each object, and the attributes characterizing relationships between objects. Our aim is to focus on the complement of two approaches, on one hand concerns the remote sensing and the image segmentation, and on the other hand concerns the knowledge discovery and the modeling. The first approach discusses how to apply an autoadaptive (non-linear) segmentation approach on a collection of such images. This method is based on the morphological transformations of opening and closing to obtain relevant and significant objects. Using this approach, we simplify and conserve the principal features and objects from the image. The second approach proposes to create a set of XML tags to model the main features elicited from the previous objects using their relationships. These tags are then exploited by querying, using topological, directional, or metrical relationships. Using this approach we can extract not only some explicit spatial information like urban areas, wooded areas and linear features such as roads or railways, but some implicit spatial information like urban organization or urban dynamics.

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“…For retrieval, we have chosen to implement through XQuery [25], [26], [27], currently the most recent XML query language, and most powerful one compared to the older ones [28], [29].…”

Section: Discussionmentioning

confidence: 99%

Very high spatial resolution images: Segmenting, modeling and knowledge discovery

Lopez-Ornelas

2009

2009 17th International Conference on Geoinformatics

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“…The query languages of [5,2,9] cannot express word proximity as in AWP and the same is true for other W3C XML query languages. The recent W3C working draft [14] and papers like [8,1,4] are expected to pave the way for the introduction of IR concepts in XQuery/XPath. Our work on AWP serves a similar goal but we have chosen to work with the simple concept of a flat document interpreted under the Boolean model of IR, instead of XML and the vector space model.…”

Section: Introductionmentioning

confidence: 99%

“…The main ideas of this paper can be transferred to languages such as [8,1,4] and this is where we concentrate our current efforts.…”

Section: Introductionmentioning

confidence: 99%

Filtering algorithms for information retrieval models with named attributes and proximity operators

Tryfonopoulos

Koubarakis

Drougas

2004

Proceedings of the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval

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In the selective dissemination of information (or publish/ subscribe) paradigm, clients subscribe to a server with continuous queries (or profiles) that express their information needs. Clients can also publish documents to servers. Whenever a document is published, the continuous queries satisfying this document are found and notifications are sent to appropriate clients. This paper deals with the filtering problem that needs to be solved efficiently by each server: Given a database of continuous queries db and a document d, find all queries q ∈ db that match d. We present data structures and indexing algorithms that enable us to solve the filtering problem efficiently for large databases of queries expressed in the model AWP which is based on named attributes with values of type text, and word proximity operators.

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“…We would like to combine approximate phrase querying and approximate structure querying as in [2,3,6,7,8,12,13].…”

Section: Future Workmentioning

confidence: 99%

“…Several proposals [3,4,7] have studied techniques for combining IR searches with document structure. As an example, the query that returns (i) text elements containing both "Mr. English" and "Mr. Coyne" and (ii) its preceding and following text elements, combines keyword search with "sibling" axis.…”

Section: Introductionmentioning

confidence: 99%

PIX: a system for phrase matching in XML documents: a demonstration

Amer-Yahia

Fernández

Srivastava

et al.

Proceedings 19th International Conference on Data Engineering (Cat. No.03CH37405)

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We present a system that enables flexible and efficient phrase matching in XML documents. Since XML allows structured and unstructured information to be interleaved, phrase matching in XML raises new challenges. Our system, named PIX, permits phrase matching in XML documents that contain "mixed content". A key feature of PIX is that users can specify which element and content to ignore when matching a phrase. PIX uses inverted indices and an efficient evaluation algorithm to compute the set of matches and returns answers where phrases, ignored tags and content are highlighted. In addition, query answers are sorted using a ranking function. PIX is implemented as an extension of GALAX, a full-fledged XQuery engine. The functionality of PIX is fully integrated into XQuery and permits a natural combination of XPath-based structure matching with phrase matching.

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XQL and proximal nodes

Cited by 24 publications

References 15 publications

Very high spatial resolution images: Segmenting, modeling and knowledge discovery

Very high spatial resolution images: Segmenting, modeling and knowledge discovery

Filtering algorithms for information retrieval models with named attributes and proximity operators

PIX: a system for phrase matching in XML documents: a demonstration

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