Query Operators Shown Beneficial for Improving Search Results

Hubert, Gilles; Cabanac, Guillaume; Sallaberry, Christian; Palacio, Damien

doi:10.1007/978-3-642-24469-8_14

Cited by 4 publications

(6 citation statements)

References 15 publications

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“…Queries are sequences of operators applied to collections [16,29]. The execution process of queries is based on the concept of state of the query process, that is a pair s = (tc; IR), where tc is a collection named Temporary Collection, while IR is a database named Intermediate Results database.…”

Section: J-co-ql Main Featuresmentioning

confidence: 99%

Why we need a Novel Framework to Integrate and Transform Heterogeneous Multi-Source Geo referenced Information : The J-Co Proposal

Bordogna¹,

Psaila²

2018

Computer Science &Amp; Information Technology (CS &Amp; IT)

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The large number of geo referenced data sets provided by Open Data portals, social media networks and created by volunteers within citizen science projects (Volunteered Geographical Information) is pushing analysts to define and develop novel frameworks for analysing these multisource heterogeneous data sets in order to derive new data sets that generate social value. For analysts, such an activity is becoming a common practice for studying, predicting and planning social dynamics. The convergence of various technologies related with data representation formats, database management and GIS (Geographical Information Systems) can enable analysts to perform such complex integration and transformation processes. JSON has become the de-facto standard for representing (possibly geo-referenced) data sets to share; NoSQL databases (and MongoDB in particular) are able to natively deal with collections of JSON objects; the GIS community has defined the GeoJSON standard, a JSON format for representing georeferenced information layers, and has extended GIS software to support it. However, all these technologies have been separately developed, consequently, there is actually a gap that shall be filled to easily manipulate GeoJSON objects by performing spatial operations. In this paper, we pursue the objective of defining both a unifying view of several NoSQL databases and a query language that is independent of specific database platforms to easily integrate and transform collections of GeoJSON objects. In the paper, we motivate the need for such a framework, named J-CO, able to execute novel high-level queries, written in the J-CO-QL language, for JSON objects and will show its possible use for generating open data sets by integrating various collections of geo-referenced JSON objects stored in different databases.

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Section: J-co-ql Main Featuresmentioning

confidence: 99%

Why we need a Novel Framework to Integrate and Transform Heterogeneous Multi-Source Geo referenced Information : The J-Co Proposal

Bordogna¹,

Psaila²

2018

Computer Science &Amp; Information Technology (CS &Amp; IT)

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“…As we did in [11], we conducted experiments on the TREC-8 [30] standard test collection. The TREC-8 corpus of newspaper articles corresponds to the kind of document units (e.g., newspaper or travelogue paragraphs) that the PIV 3 engine is expected to retrieve.…”

Section: Topical Multi-criteria Irmentioning

confidence: 99%

“…We demonstrated the benefits of query operators (+ and^) on regular topics in [11]. Here, because topics contain few terms and none that can be associated with exclusion or demotion roles, we propose to use the narrative part to extend each topic title with new terms.…”

Section: Topical Multi-criteria Irmentioning

confidence: 99%

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Do Expressive Geographic Queries Lead to Improvement in Retrieval Effectiveness?

Palacio

Sallaberry

Cabanac

et al. 2012

Lecture Notes in Geoinformation and Cartography

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Abstract. In an information retrieval (IR) context, users usually issue queries with few terms and no operators (e.g., and, or, +). However, most of users' information needs involve more expressiveness (e.g., 'Potato famine in Ireland, but not in Cork' ). Our work deals with this category of queries that may be processed by geographic IR (GIR) systems to parse digital libraries according to spatial, temporal and topical criteria. We propose a GIR framework that supports expressive queries and aggregates results of a multi-criteria search. We also conduct experiments to verify that this approach improves the effectiveness of such search engines (improvement of 27% for topical criteria only, and of 54% for spatial and temporal criteria).

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“…In this study, experienced PubMed users were defined as users who used advanced PubMed IR functions for query formulation. The proper use of IR functions (described in the next section) is key for efficient and effective PubMed searches [ 6 , 8 , 22 - 27 ] because, unlike Google, PubMed does not sort search results by relevance. Studies have shown that experienced users are more likely to use IR functions than novice users.…”

Section: Introductionmentioning

confidence: 99%

Analysis of PubMed User Sessions Using a Full-Day PubMed Query Log: A Comparison of Experienced and Nonexperienced PubMed Users

Yoo¹,

Mosa²

2015

JMIR Med Inform

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BackgroundPubMed is the largest biomedical bibliographic information source on the Internet. PubMed has been considered one of the most important and reliable sources of up-to-date health care evidence. Previous studies examined the effects of domain expertise/knowledge on search performance using PubMed. However, very little is known about PubMed users’ knowledge of information retrieval (IR) functions and their usage in query formulation.ObjectiveThe purpose of this study was to shed light on how experienced/nonexperienced PubMed users perform their search queries by analyzing a full-day query log. Our hypotheses were that (1) experienced PubMed users who use system functions quickly retrieve relevant documents and (2) nonexperienced PubMed users who do not use them have longer search sessions than experienced users.MethodsTo test these hypotheses, we analyzed PubMed query log data containing nearly 3 million queries. User sessions were divided into two categories: experienced and nonexperienced. We compared experienced and nonexperienced users per number of sessions, and experienced and nonexperienced user sessions per session length, with a focus on how fast they completed their sessions.ResultsTo test our hypotheses, we measured how successful information retrieval was (at retrieving relevant documents), represented as the decrease rates of experienced and nonexperienced users from a session length of 1 to 2, 3, 4, and 5. The decrease rate (from a session length of 1 to 2) of the experienced users was significantly larger than that of the nonexperienced groups.ConclusionsExperienced PubMed users retrieve relevant documents more quickly than nonexperienced PubMed users in terms of session length.

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Query Operators Shown Beneficial for Improving Search Results

Cited by 4 publications

References 15 publications

Why we need a Novel Framework to Integrate and Transform Heterogeneous Multi-Source Geo referenced Information : The J-Co Proposal

Why we need a Novel Framework to Integrate and Transform Heterogeneous Multi-Source Geo referenced Information : The J-Co Proposal

Do Expressive Geographic Queries Lead to Improvement in Retrieval Effectiveness?

Analysis of PubMed User Sessions Using a Full-Day PubMed Query Log: A Comparison of Experienced and Nonexperienced PubMed Users

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