Search results

Geographical query formulation is one of the key difficulties for users in search engines. The purpose of this study is to improve geographical search by proposing a novel geographical query reformulation (GQR) technique using a geographical taxonomy and word senses.

This work introduces an approach for GQR, which combines a method of query components separation that uses GeoNames, a technique for reformulating these components using WordNet and a geographic taxonomy constructed using the latent semantic analysis method.

The proposed approach was compared to two methods from the literature, using the mean average precision (MAP) and the precision at 20 documents (P@20). The experimental results show that it outperforms the other techniques by 15.73% to 31.21% in terms of P@20 and by 17.81% to 35.52% in terms of MAP.

According to the experimental results, the best created taxonomy using the geographical adjacency taxonomy builder contains 7.67% of incorrect links. This paper believes that using a very big amount of data for taxonomy building can give better results. Thus, in future work, this paper intends to apply the approach in a big data context.

Despite this, the reformulation of geographical queries using the new proposed approach considerably improves the precision of queries and retrieves relevant documents that were not retrieved using the original queries. The strengths of the technique lie in the facts of reformulating both thematic and spatial entities and replacing the spatial entity of the query with terms that explain the intent of the query more precisely using a geographical taxonomy.

Collaborative information search (CIS) is a growing and significant research area. Query formulation and reformulation is an important search strategy in information search. However, limited research has investigated query behavior during CIS. The purpose of this paper is to characterize collaborative query reformulation (CQR) by exploring the sources of collaborative query (CQ) terms and the types and patterns of CQR in the context of tourism information search.

An empirical study was designed to investigate search query reformulation as tourists performed CIS on a devised interface. A total of 36 participants (in 18 pairs) took part in the study; data were documented in pre- and post-search questionnaires, search logs and chat logs.

The findings show that participants intermixed individual search and collaborative search during CIS. Participants constructed CQ terms mainly by selecting terms from individual search queries and discussion chat logs. Eight types of CQR were identified, with specialization (82 percent) accounting for the most used search tactics. At most times, participants were found to add terms to the previous query. Findings demonstrated 27 specific CQR patterns; in excess of two-third participants (69 percent) took only one move to reformulate CQ by adding terms, or replacing/using new words.

The results of this research can be used to inform the design of search systems supporting collaborative querying in CIS.

This study is highlighting an important research direction of CQ reformulation in collaborative search while previous studies of the topic are limited, comparing to the vast body of work on query reformulation in individual information search using regular search systems.

Users' search logs are implicit feedbacks on how searchers interact with online information retrieval (IR) systems. The purpose of this paper is to analyze search query reformulation (SQR) patterns of University of Dar es Salaam remote OPAC users.

Qualitative and quantitative analysis of transaction logs were employed to ascertain the characteristics of search queries and the patterns in which remote OPAC users reformulate their search queries. The study covered a period of six months, commencing from January to June 2019.

A total of 30,474 search hits were submitted by remote OPAC users during the period under study. Individuals from academic and research institutions, computing consortia, and telecommunication companies are the main users of the system. Most of the searches originated from North America and Europe, with few searches coming from China and India. Besides improving search results, SQRs are linked with the existence of multiple information demands as manifested by the use of heterogeneous headwords within individual search episodes.

Data collected covered only six months. Similarly, it was however not possible to analyze users' search query formulation within specific contexts such as task-based information searching.

A query recommendation system should be integrated into the OPAC functionalities to improve users' search experiences. Alternatively, there should be a migration to a new system that offers more advanced search features and functionalities.

The study has contributed new insights in SQR studies particularly on how non-institutional affiliated users translate their information needs into search queries during information searching processes.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-09-2020-0389

To investigate and identify the patterns of interaction between searchers and search engine during web searching.

The authors examined 2,465,145 interactions from 534,507 users of Dogpile.com submitted on May 6, 2005, and compared query reformulation patterns. They investigated the type of query modifications and query modification transitions within sessions.

The paper identifies three strong query reformulation transition patterns: between specialization and generalization; between video and audio, and between content change and system assistance. In addition, the findings show that web and images content were the most popular media collections.

This research sheds light on the more complex aspects of web searching involving query modifications.

Aims to present a comparison and evaluation of four user interfaces of web‐based e‐journals (Science Direct, ProQuest Direct, EBSCO Host and Emerald).

The systems were assessed in an expert study according to accepted guidelines regarding user friendliness and functionality. User friendliness features studied were: language(s) and type(s) of interface; navigation options; personalization; and screen features. Functions inspected were: database selection; query formulation and reformulation; results manipulation; and help.

Many similarities were found, but some differences among the systems were also discovered and analysed in detail. The greatest differences were found in the area of query formulation, and between the interface languages and types.

The user interfaces of four full‐text IR systems offering e‐journals which are accessible at the University of Ljubljana are surveyed.

The interfaces are surveyed and assessed in order to discover their characteristics, advantages, and potential downsides and/or mistakes which may hinder use by an average user.

The study serves as a basis for a subsequent user study of the information behaviour of the users of these systems.

Web search engines are frequently used by people to locate information on the Internet. However, not all queries have an informational goal. Instead of information, some people may be looking for specific web sites or may wish to conduct transactions with web services. This paper aims to focus on automatically classifying the different user intents behind web queries.

For the research reported in this paper, 130,000 web search engine queries are categorized as informational, navigational, or transactional using a k‐means clustering approach based on a variety of query traits.

The research findings show that more than 75 percent of web queries (clustered into eight classifications) are informational in nature, with about 12 percent each for navigational and transactional. Results also show that web queries fall into eight clusters, six primarily informational, and one each of primarily transactional and navigational.

This study provides an important contribution to web search literature because it provides information about the goals of searchers and a method for automatically classifying the intents of the user queries. Automatic classification of user intent can lead to improved web search engines by tailoring results to specific user needs.

The paper discusses how web search engines can use automatically classified user queries to provide more targeted and relevant results in web searching by implementing a real time classification method as presented in this research.

This research investigates a new application of a method for automatically classifying the intent of user queries. There has been limited research to date on automatically classifying the user intent of web queries, even though the pay‐off for web search engines can be quite beneficial.

As voice search has progressively become a new way of information acquisition and human–computer interaction, this paper aims to explore the users' voice search behavior in human–vehicle interaction.

This study employed mixed research methods, including questionnaires and interviews. A total of 151 Amazon MTurk volunteers were recruited to complete a questionnaire based on their most recent and impressive voice search experience. After the questionnaire, this paper conducted an online interview with the participants.

This paper studied users' voice search behavior characteristics in the context of the human–vehicle interaction and analyzed the voice search content, search need, search motivation and user satisfaction. In addition, this paper studied the barriers and suggestions for voice search in human–vehicle interaction through a content analysis of the interviews.

This paper's analysis of users' barriers and suggestions has a specific reference value for optimizing the voice search interaction system and improving the service.

This study is exploratory research that seeks to identify users' voice search needs and tasks and investigate voice search satisfaction in human–vehicle interaction context.

This exploratory study aims to help contribute to the understanding of online information search behaviour of PhD students from different humanities fields, with a focus on subject searching.

The methodology is based on a semi-structured interview within which the participants are asked to conduct both a controlled search task and a free search task. The sample comprises eight PhD students in several humanities disciplines at Linnaeus University, a medium-sized Swedish university from 2020.

Most humanities PhD students in the study have received training in information searching, but it has been too basic. Most rely on web search engines like Google and Google Scholar for publications' search, and university's discovery system for known-item searching. As these systems do not rely on controlled vocabularies, the participants often struggle with too many retrieved documents that are not relevant. Most only rarely or never use disciplinary bibliographic databases. The controlled search task has shown some benefits of using controlled vocabularies in the disciplinary databases, but incomplete synonym or concept coverage as well as user unfriendly search interface present hindrances.

The paper illuminates an often-forgotten but pervasive challenge of subject searching, especially for humanities researchers. It demonstrates difficulties and shows how most PhD students have missed finding an important resource in their research. It calls for the need to reconsider training in information searching and the need to make use of controlled vocabularies implemented in various search systems with usable search and browse user interfaces.

Effective land use management in lesser developed countries is problematic due to a variety of factors including inexperience and turnover of decision makers, lack of communication among experts in functional areas, and scattered or missing data needed by managers to make informed decisions. This paper describes a “first step” approach toward the solution of these problems that was implemented in the Dominican Republic. The paper introduces a framework used to organize and facilitate the sharing of data needed for land use decision across multiple disciplines. The framework provided the basis for the development of a prototype agricultural geographic decision support system for use in the Dominican Republic. This system is unique in that it combines concepts from semantic data modeling and database design, geographic information systems, and knowledge‐based systems.