Search results

This study aims to examine manually formulated queries and automatic query generation in an early phase of a patent “prior art” search.

The study was performed partly within a patent domain setting, involving three professional patent examiners, and partly in the context of the CLEF 2009 Intellectual Property (CLEF-IP) track. For the exploratory study of user-based query formulation, three patent examiners performed the same three simulated real-life patent tasks. For the automatic query generation, a simple term-weighting algorithm based on the RATF formula was used. The manually and automatically created queries were compared to analyse what kinds of keywords and from which parts of the patent documents were selected.

For user-formulated queries, it was found that patent documents were read in a specific order of importance and that the time varied. Annotations and collaboration were made while reading and selecting/ranking terms. Ranking terms was experienced to be harder than selecting terms. For the automatic formulated queries, it was found that the term frequencies used in the RATF alone will not quite approximate what terms will be judged as relevant query terms by the users. Simultaneously, the results suggest that developing a query generation tool for generating initial queries based on patent documents is feasible.

These preliminary but informative results need to be viewed in the light that only three patent experts were observed and that a small set of topics was used.

It is usually difficult to get access to the setting of the patent domain and the results of the study show that the methodology provided a feasible way to study manual and the manual query formulation of the patent engineer.

With an increase in the amount of multilingual content on the World Wide Web, users are often striving to access information provided in a language of which they are non-native speakers. The purpose of this paper is to present a comprehensive study of user profile representation techniques and investigate their use in personalized cross-language information retrieval (CLIR) systems through the means of personalized query expansion.

The user profiles consist of weighted terms computed by using frequency-based methods such as tf-idf and BM25, as well as various latent semantic models trained on monolingual documents and cross-lingual comparable documents. This paper also proposes an automatic evaluation method for comparing various user profile generation techniques and query expansion methods.

Experimental results suggest that latent semantic-weighted user profile representation techniques are superior to frequency-based methods, and are particularly suitable for users with a sufficient amount of historical data. The study also confirmed that user profiles represented by latent semantic models trained on a cross-lingual level gained better performance than the models trained on a monolingual level.

Previous studies on personalized information retrieval systems have primarily investigated user profiles and personalization strategies on a monolingual level. The effect of utilizing such monolingual profiles for personalized CLIR remains unclear. The current study fills the gap by a comprehensive study of user profile representation for personalized CLIR and a novel personalized CLIR evaluation methodology to ensure repeatable and controlled experiments can be conducted.

It is crucial for information retrieval systems to learn more about what users search for in order to fulfil the intent of searches. This paper introduces query taxonomy generation, which attempts to organise users’ queries into a hierarchical structure of topic classes. Such a query taxonomy provides a basis for the in‐depth analysis of users’ queries on a larger scale and can benefit many information retrieval systems. The proposed approach to this problem consists of two computational processes: hierarchical query clustering to generate a query taxonomy from scratch, and query categorisation to place newly‐arrived queries into the taxonomy. The results of the preliminary experiment have shown the potential of the proposed approach in generating taxonomies for queries, which may be useful in various Web information retrieval applications.

With the rapid development of materials informatics and the Semantic Web, the semantic-driven solution has emerged to improve traditional query technology, which is hard to discover implicit knowledge from materials data. However, it is a nontrivial thing for materials scientists to construct a semantic query, and the query results are usually presented in RDF/XML format which is not convenient for users to understand. This paper aims to propose an approach to construct semantic query and visualize the query results for metallic materials domain.

The authors design a query builder to generate SPARQL query statements automatically based on domain ontology and query conditions inputted by users. Moreover, a semantic visualization model is defined based on the materials science tetrahedron to support the visualization of query results in an intuitive, dynamic and interactive way.

Based on the Semantic Web technology, the authors design an automatic semantic query builder to help domain experts write the normative semantic query statements quickly and simply, as well as a prototype (named MatViz) is developed to visually show query results, which could help experts discover implicit knowledge from materials data. Moreover, the experiments demonstrate that the proposed system in this paper can rapidly and effectively return visualized query results over the metallic materials data set.

This paper mainly discusses an approach to support semantic query and visualization of metallic materials data. The implementation of MatViz will be a meaningful work for the research of metal materials data integration.

This purpose of this paper is to propose a recommendation approach for information retrieval.

Relevant results are presented on the basis of a novel data structure named FPT‐tree, which is used to get common interests. Then, data is trained by using a partial back‐propagation neural network. The learning is guided by users' click behaviors.

Experimental results have shown the effectiveness of the approach.

The approach attempts to integrate metric of interests (e.g., click behavior, ranking) into the strategy of the recommendation system. Relevant results are first presented on the basis of a novel data structure named FPT‐tree, and then, those results are trained through a partial back‐propagation neural network. The learning is guided by users' click behaviors.

With the rapid spread of smartphones and tablets, it is becoming necessary for web developers to create responsive web pages which are visually appealing on devices of various sizes. However, building responsive UIs is a very challenging task, requiring deep knowledge of HTML and CSS. This paper aims to propose an approach to generate responsive web pages using SuperSQL, which is an extension of SQL that can format data retrieved from a database into various kinds of structured documents.

By incorporating the methodology of bootstrap, a grid-based framework for front-end development, the authors have made it possible to create responsive web pages from simple SuperSQL queries. In addition, by utilizing SuperSQL’s unique feature that can describe the structure of the output web page, the authors have proposed and implemented a mechanism to automatically optimize the web content’s size and position.

In the evaluation, the authors created some actual web applications with and without the use of SuperSQL and compared the code amount (number of lines). As a result, when using the proposed system, the amount of code was reduced to about 1/5. The authors also compared the layout generated by the proposed automatic layout generation mechanism with the responsive layout that was generated manually. As a result, the automatic layout generation mechanism created the same layout as the manually created layout 74.8 per cent of the time, and the user satisfaction level turned out to be 85.8 per cent.

The way to generate a responsive HTML by using a single SuperSQL query, and the mechanism for automatic responsive layout generation.

Sizing functions are crucial inputs for unstructured mesh generation since they determine the element distributions of resulting meshes to a large extent. Meanwhile, automating the procedure of creating a sizing function is a prerequisite to set up a fully automatic mesh generation pipeline. In this paper, an automatic algorithm is proposed to create a high-quality sizing function for an unstructured surface and volume mesh generation by using a triangular mesh as the background mesh.

A practically efficient and effective solution is developed by using local operators carefully to re-mesh the tessellation of the input Computer Aided Design (CAD) models. A nonlinear programming (NLP) problem has been formulated to limit the gradient of the sizing function, while in this study, the object function of this NLP is replaced by an analytical equation that predicts the number of elements. For the query of the sizing value, an improved algorithm is developed by using the axis-aligned bounding box (AABB) tree structure.

The local operations of re-meshing could effectively and efficiently resolve the banding issue caused by using the default tessellation of the model to define a sizing function. Experiments show that the solution of the revised NLP, in most cases, could provide a better solution at the lower cost of computational time. With the help of the AABB tree, the sizing function defined at a surface background mesh can be also used as the input of volume mesh generation.

Theoretical analysis reveals that the construction of the initial sizing function could be reduced to the solution of an optimization problem. The definitions of the banding elements and surface proximity are also given. Under the guidance of this theoretical analysis, re-meshing and ray-casting technologies are well-designed to initial the sizing function. Smoothing with the revised NLP and querying by the AABB tree, the paper provides an automatic method to get a high-quality sizing function for both surface and volume mesh generation.

Asian languages such as Japanese, Korean and in particular Chinese, are beginning to gain popularity in the information retrieval (IR) domain. The quality of IR systems has traditionally been judged by the system’s retrieval effectiveness which, in turn, is commonly measured by data recall and data precision. This paper proposes and describes a process for generating an automatic Chinese thesaurus that can be used to provide related terms to a user’s queries to enhance retrieval effectiveness. In the absence of existing automatic Chinese thesauri, techniques used in English thesaurus generation have been evaluated and adapted to generate a Chinese equivalent. The automatic thesaurus is generated by computing the co‐occurrence values between domain‐specific terms found in a document collection. These co‐occurrence values are in turn derived from the term and document frequencies of the terms. A set of experiments was subsequently carried out on a document test set to evaluate the applicability of the thesaurus. Results obtained from these experiments confirmed that such an automatic generated thesaurus is able to improve the retrieval effectiveness of a Chinese IR system.

This paper introduces an approach to minimize the total designer effort for building XML data integration systems. Since fully automatic schema mapping generation is infeasible, in our view such an approach can be used as a semi‐automatic tool for XML schemas mediation. A method is proposed to query XML documents through a mediation layer. Such a layer is introduced to describe the mappings between global XML schema and local heterogeneous XML schemas. It produces a uniform interface over the local XML data sources, and provides the required functionality to query these sources in a uniform way. It involves two important units: the XML Metadata Document (XMD) and the Query Translator. The XMD is an XML document containing metadata, in which the mappings between global and local schemas are defined. The XML Query Translator which is an integral part of the system is introduced to translate a global user query into local queries by using the mappings that are defined in the XMD.

There is a huge amount of information and data stored in publicly available online databases that consist of large text files accessed by Boolean search techniques. It is widely held that less use is made of these databases than could or should be the case, and that one reason for this is that potential users find it difficult to identify which databases to search, to use the various command languages of the hosts and to construct the Boolean search statements required. This reasoning has stimulated a considerable amount of exploration and development work on the construction of search interfaces, to aid the inexperienced user to gain effective access to these databases. The aim of our paper is to review aspects of the design of such interfaces: to indicate the requirements that must be met if maximum aid is to be offered to the inexperienced searcher; to spell out the knowledge that must be incorporated in an interface if such aid is to be given; to describe some of the solutions that have been implemented in experimental and operational interfaces; and to discuss some of the problems encountered. The paper closes with an extensive bibliography of references relevant to online search aids, going well beyond the items explicitly mentioned in the text. An index to software appears after the bibliography at the end of the paper.