A Linguistic Multi-level Weighted Query Language to Represent User Information Needs

2007 ◽  
Author(s):  
Enrique Herrera-Viedma ◽  
Antonio G. Lopez-Herrera ◽  
Sergio Alonso ◽  
Carlos Porcel ◽  
Francisco J. Cabrerizo
Keyword(s):  
Information Needs ◽  
Query Language ◽  
Multi Level

Multi-Resolution Modeling of High Speed Railway Infrastructure for Train Operation Simulation

2011 ◽  
Vol 97-98 ◽  
pp. 560-565 ◽  
Author(s):  
Xi Jiang ◽  
Xue Sheng Ji ◽  
Jun Liu
Keyword(s):  
Simulation Model ◽  
High Speed ◽  
Road Network ◽  
Information Needs ◽  
Logic Function ◽  
Railway Infrastructure ◽  
Railway Signal ◽  
Train Operation ◽  
Multi Level ◽  
Different Levels

This paper analyzes the railway infrastructure simulation demands in train operation and organization at different levels. It takes the rail road network topology model and the railway signal system model as the core to build a multi-resolution-based simulation model architecture of the railway infrastructure. According to different information needs of railway infrastructure simulation model, it proposes a Hierarchical model achieving logic function of signaling system, and studies the signal system’s multi-resolution simulation methods through multi-level logic block configuration. According to the space information requirement of different simulation levels, the paper builds a multi-resolution rail road network mode.

scholarly journals Educating PhD students for knowledge-driven society

2021 ◽  
Author(s):  
Jozika Dolenc ◽  
Oliver Renn ◽  
Leo Betschart ◽  
Joachim Schnabl
Keyword(s):  
Information Needs ◽  
Scientific Information ◽  
Daily Activities ◽  
Digital Tools ◽  
Knowledge Generation ◽  
Institutions Of Higher Education ◽  
Critical Choice ◽  
Multi Level ◽  
Course Features ◽  
Extensive List

Universities educate students for working in knowledge-driven societies. Whereas subject-related knowledge is part of every curriculum, institutions of higher education fail to teach systematically how to utilize and benefit from today’s variety of digital tools. Students and researchers are mostly unaware of what they lack to work more effectively and efficiently and to benefit from existing knowledge. Since this lack of awareness is not obvious to students and researchers (unknown unknowns; you cannot miss something that you do not know), it is difficult to convince them that there is a gap that needs to be filled. In 2014, we decided to tackle this problem by creating and developing the course “Scientific Information Retrieval & Management in Life Sciences and Chemistry”. The unique 2 ECTS course features a multi-level approach to obtain and employ scientific information and to get students information savvy. On one hand, the course demonstrates the bigger picture: We discuss the aspects of scientific writing and publishing, critical choice of data sources, patents, visualisation and design, text mining and data pipelining, knowledge generation, outreach and impact of publications. On the other hand, we highlight an extensive list of field-proven tools that can assist researchers in their daily activities. We also wanted to foster a lasting impact on how students utilize databases, tools, software,and web services. Thus, at the end of the course students have to write an essay describing their current information workflow or their (un)met information needs. These essays confirm and explain how the students changed their information use, and which parts of the course they may have not understood. Moreover, essays that describe unmet information needs allow us to explore possible solutions and to work with our vendors. In our talk, we will share the concept for the course and report on our experiences.

scholarly journals SchenQL: in-depth analysis of a query language for bibliographic metadata

2021 ◽  
Author(s):  
Christin Katharina Kreutz ◽  
Michael Wolz ◽  
Jascha Knack ◽  
Benjamin Weyers ◽  
Ralf Schenkel
Keyword(s):  
Information Needs ◽  
User Study ◽  
Query Language ◽  
Information Access ◽  
Domain Experts ◽  
Domain Specific ◽  
Complex Information ◽  
Depth Analysis ◽  
Information Exploration ◽  
High Level

AbstractInformation access to bibliographic metadata needs to be uncomplicated, as users may not benefit from complex and potentially richer data that may be difficult to obtain. Sophisticated research questions including complex aggregations could be answered with complex SQL queries. However, this comes with the cost of high complexity, which requires for a high level of expertise even for trained programmers. A domain-specific query language could provide a straightforward solution to this problem. Although less generic, it can support users not familiar with query construction in the formulation of complex information needs. In this paper, we present and evaluate SchenQL, a simple and applicable query language that is accompanied by a prototypical GUI. SchenQL focuses on querying bibliographic metadata using the vocabulary of domain experts. The easy-to-learn domain-specific query language is suitable for domain experts as well as casual users while still providing the possibility to answer complex information demands. Query construction and information exploration are supported by a prototypical GUI. We present an evaluation of the complete system: different variants for executing SchenQL queries are benchmarked; interviews with domain-experts and a bipartite quantitative user study demonstrate SchenQL’s suitability and high level of users’ acceptance.

scholarly journals Educating PhD students for knowledge-driven society

2020 ◽  
Author(s):  
Oliver Renn ◽  
Jozica Dolenc ◽  
Leo Betschart ◽  
Joachim Schnabl
Keyword(s):  
Information Needs ◽  
Scientific Information ◽  
Daily Activities ◽  
Digital Tools ◽  
Knowledge Generation ◽  
Institutions Of Higher Education ◽  
Critical Choice ◽  
Multi Level ◽  
Course Features ◽  
Extensive List

Universities educate students for working in knowledge-driven societies. Whereas subject-related knowledge is part of every curriculum, institutions of higher education fail to teach systematically how to utilize and benefit from today’s variety of digital tools. Students and researchers are mostly unaware of what they lack to work more effectively and efficiently and to benefit from existing knowledge. Since this lack of awareness is not obvious to students and researchers (unknown unknowns; you cannot miss something that you do not know), it is difficult to convince them that there is a gap that needs to be filled.  In 2014, we decided to tackle this problem by creating and developing the course “Scientific Information Retrieval & Management in Life Sciences and Chemistry”. The unique 2 ECTS course features a multi-level approach to obtain and employ scientific information and to get students information savvy. On one hand, the course demonstrates the bigger picture: We discuss the aspects of scientific writing and publishing, critical choice of data sources, patents, visualisation and design, text mining and data pipelining, knowledge generation, outreach and impact of publications. On the other hand, we highlight an extensive list of field-proven tools that can assist researchers in their daily activities.  We also wanted to foster a lasting impact on how students utilize databases, tools, software, and web services. Thus, at the end of the course students have to write an essay describing their current information workflow or their (un)met information needs. These essays confirm and explain how the students changed their information use, and which parts of the course they may have not understood. Moreover, essays that describe unmet information needs allow us to explore possible solutions and to work with our vendors. In our talk, we will share the concept for the course and report on our experiences. 

scholarly journals Peringkasan Multi-dokumen menggunakan Metode Pengelompokkan berbasis Hirarki dengan Multi-level Divisive Coefficient

2018 ◽  
Vol 5 (6) ◽  
pp. 697
Author(s):  
Muhamad Mustamiin ◽  
Ahmad Lubis Ghozali ◽  
Muhammad Lukman Sifa
Keyword(s):  
Information Retrieval ◽  
Hierarchical Clustering ◽  
Information Needs ◽  
Document Summarization ◽  
Group A ◽  
Multi Level ◽  
F Measure ◽  
Need For Information

<p class="Abstrak">Peringkasan merupakan salah satu bagian dari perolehan informasi yang bertujuan untuk mendapatkan informasi secara cepat dan efisien dengan membuat intisari dari suatu dokumen. Dokumen-dokumen khususnya dokumen laporan setiap hari semakin bertambah seiring dengan bertambahnya pelaksanaan suatu kegiatan atau acara. Kebutuhan informasi yang semakin cepat, jumlah dokumen yang semakin bertambah banyak membuat kebutuhan akan adanya peringkasan dokumen semakin tinggi. Peringkasan yang digunakan untuk meringkas lebih dari satu dokumen disebut peringkasan multi-dokumen. Untuk mencegah adanya penyampaian informasi yang berulang pada peringkasan multi-dokumen, maka proses pengelompokkan diperlukan untuk menjamin bahwa informasi yang disampaikan bervariasi dan mencakup semua bagian dari dokumen-dokumen tersebut. Pengelompokkan hirarki dengan multi-level <em>divisive</em> <em>coefficient</em> dapat digunakan untuk mengelompokkan suatu bagian/kalimat dalam dokumen-dokumen dengan bervariasi dan mendalam yang disesuaikan dengan tingkat kebutuhan informasi dari pengguna. Bedasarkan dari tingkat kompresi peringkasan yang berbeda-beda, peringkasan menggunakan pengelompokkan hirarki dengan multi-level <em>divisive</em> <em>coefficient</em> dapat menghasilkan hasil peringkasan yang cukup baik dengan nilai f-measure sebesar 0,398 sementara nilai f-measure peringkasan dengan satu level <em>divisive</em> <em>coefficient</em> hanya mencapai 0,335.</p><p class="Judul2"><strong><em>Abstract</em></strong></p><p class="Abstract"><em>Summarization is one part of the information retrieval that aims to obtain information quickly and efficiently by making the essence of a document. Documents, especially document reports every day increasing as the implementation of an event. The need for information is getting faster, the increasing number of documents makes the need for document summaries is getting higher. Summarization used to summarize more than one document is called multi-document summarization. To prevent repetitive information from being submitted to multi-document summarization, the grouping process is necessary to ensure that the information submitted varies and covers all parts of the documents. Hierarchical clustering with multi-level divisive coefficient can be used to group a part / sentence in documents with varying and depth adjusted to the level of information needs of the user. Based on different compression levels of summarization, summarization using hierarchical clustering with multi-level divisive coefficient can produce a fairly good summary result with f-measure value of 0.398 while the f-measure summarization value with one level of divisive coefficient only reaches 0.335.</em></p>

A semantic-syntax model for XML query construction

2017 ◽  
Vol 13 (2) ◽  
pp. 155-172 ◽  
Author(s):  
Keng Hoon Gan ◽  
Keat Keong Phang
Keyword(s):  
Information Needs ◽  
Query Language ◽  
Query Languages ◽  
Target Language ◽  
Lower Percentage ◽  
Content Type ◽  
Semantic Query ◽  
Query Structure ◽  
Information Requests ◽  
Query Model

Purpose When accessing structured contents in XML form, information requests are formulated in the form of special query languages such as NEXI, Xquery, etc. However, it is not easy for end users to compose such information requests using these special queries because of their complexities. Hence, the purpose of this paper is to automate the construction of such queries from common query like keywords or form-based queries. Design/methodology/approach In this paper, the authors address the problem of constructing queries for XML retrieval by proposing a semantic-syntax query model that can be used to construct different types of structured queries. First, a generic query structure known as semantic query structure is designed to store query contents given by user. Then, generation of a target language is carried out by mapping the contents in semantic query structure to query syntax templates stored in knowledge base. Findings Evaluations were carried out based on how well information needs are captured and transformed into a target query language. In summary, the proposed model is able to express information needs specified using query like NEXI. Xquery records a lower percentage because of its language complexity. The authors also achieve satisfactory query construction rate with an example-based method, i.e. 86 per cent (for NEXI IMDB topics) and 87 per cent (NEXI Wiki topics), respectively, compare to benchmark of 78 per cent by Sumita and Iida in language translation. Originality/value The proposed semantic-syntax query model allows flexibility of accommodating new query language by separating the semantic of query from its syntax.

CBench

2021 ◽  
Vol 14 (8) ◽  
pp. 1325-1337
Author(s):  
Abdelghny Orogat ◽  
Isabelle Liu ◽  
Ahmed El-Roby
Keyword(s):  
Structural Properties ◽  
Information Needs ◽  
Question Answering ◽  
Query Language ◽  
Small Subset ◽  
Question Answering System ◽  
Fine Grained ◽  
Question Answering Systems ◽  
Knowledge Graphs ◽  
Single Number

Recently, there has been an increase in the number of knowledge graphs that can be only queried by experts. However, describing questions using structured queries is not straightforward for non-expert users who need to have sufficient knowledge about both the vocabulary and the structure of the queried knowledge graph, as well as the syntax of the structured query language used to describe the user's information needs. The most popular approach introduced to overcome the aforementioned challenges is to use natural language to query these knowledge graphs. Although several question answering benchmarks can be used to evaluate question-answering systems over a number of popular knowledge graphs, choosing a benchmark to accurately assess the quality of a question answering system is a challenging task. In this paper, we introduce CBench, an extensible, and more informative benchmarking suite for analyzing benchmarks and evaluating question answering systems. CBench can be used to analyze existing benchmarks with respect to several fine-grained linguistic, syntactic, and structural properties of the questions and queries in the benchmark. We show that existing benchmarks vary significantly with respect to these properties deeming choosing a small subset of them unreliable in evaluating QA systems. Until further research improves the quality and comprehensiveness of benchmarks, CBench can be used to facilitate this evaluation using a set of popular benchmarks that can be augmented with other user-provided benchmarks. CBench not only evaluates a question answering system based on popular single-number metrics but also gives a detailed analysis of the linguistic, syntactic, and structural properties of answered and unanswered questions to better help the developers of question answering systems to better understand where their system excels and where it struggles.

TOWARDS AN EFFICIENT RDF DATASET SLICING

2013 ◽  
Vol 07 (04) ◽  
pp. 455-477 ◽  
Author(s):  
EDGARD MARX ◽  
TOMMASO SORU ◽  
SAEEDEH SHEKARPOUR ◽  
SÖREN AUER ◽  
AXEL-CYRILLE NGONGA NGOMO ◽  
...  
Keyword(s):  
Information Needs ◽  
Query Language ◽  
Open Data ◽  
Linked Open Data ◽  
Connected Subgraph ◽  
Triple Store ◽  
Subgraph Pattern ◽  
Order Of Magnitude ◽  
Efficient Processing ◽  
Description Framework

Over the last years, a considerable amount of structured data has been published on the Web as Linked Open Data (LOD). Despite recent advances, consuming and using Linked Open Data within an organization is still a substantial challenge. Many of the LOD datasets are quite large and despite progress in Resource Description Framework (RDF) data management their loading and querying within a triple store is extremely time-consuming and resource-demanding. To overcome this consumption obstacle, we propose a process inspired by the classical Extract-Transform-Load (ETL) paradigm. In this article, we focus particularly on the selection and extraction steps of this process. We devise a fragment of SPARQL Protocol and RDF Query Language (SPARQL) dubbed SliceSPARQL, which enables the selection of well-defined slices of datasets fulfilling typical information needs. SliceSPARQL supports graph patterns for which each connected subgraph pattern involves a maximum of one variable or Internationalized resource identifier (IRI) in its join conditions. This restriction guarantees the efficient processing of the query against a sequential dataset dump stream. Furthermore, we evaluate our slicing approach on three different optimization strategies. Results show that dataset slices can be generated an order of magnitude faster than by using the conventional approach of loading the whole dataset into a triple store.

scholarly journals A Web-Based Aggregate Information Portal

2021 ◽  
Vol 5 (3) ◽  
pp. 14-22
Author(s):  
Donatus I. Bayem ◽  
Henry O. Osuagwu ◽  
Chimezie F. Ugwu
Keyword(s):  
Programming Languages ◽  
Web Application ◽  
Information Needs ◽  
Relational Databases ◽  
Query Language ◽  
Web Portal ◽  
Web Based ◽  
Information Portal ◽  
Aggregate Information ◽  
The Web

A Web portal aggregates an array of information for a target audience and affords a variety of services including search engines, directories, news, e-mail, and chat rooms, and they have evolved to provide a customized gateway to Web information. Also, a high level of personalization and customization has been possible. The portal concept could further be established to function as a classy Web interface that can serves as sustenance for variety of the task performance. The aggregate information Web portal will serve as portals for the information needs of users on the web. The Web based portal enable marketing of users broadly across a wide variety of interests. Most of the popular usage of the Web based aggregate information portal probably refers to the visual and user interface (UI) design of a Web site. It is a crucial aspect since the visitor is often more impressed with looks of website and easy to use rather than about the technologies and techniques that are used behind the scenes, or the operating system that runs on the web server. In other words, it just does not matter what technologies that is involved in creating, when the site is hard to use and easy to forget. This paper explores the factors that must be painstaking during the design and development of a Web based aggregate information portal. Design as a word in the context of a Web application can mean many things. A working Web based aggregate information portal, kaseremulticoncept was developed to support the various users’ task performances. A number of technologies was studied and implemented in this research, which includes multi-tier architecture, server and client side scripting techniques and technologies such as PHP programming languages and relational databases such as MySQL, Structured Query language (SQL) and XAMPP Server.

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