Query Expansion Using Conceptual Knowledge in Computer Science

Raza, Muhammad Ahsan; Rahmah, Mokhtar; Ahmad, Noraziah; Hamid, Roslina Abd; Zainuddin, Fauziah; Azhar, Ahmad Nor

doi:10.1166/asl.2018.12965

Cited by 4 publications

(2 citation statements)

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“…Ontology is a source of explicit specification of domain concepts, properties, constraints and security [1]. The ontology knowledge helps to uncover the implicit domain semantics which can be used in various intelligent systems such as query expansion [2,3] and expert systems [4,5].…”

Section: Introductionmentioning

confidence: 99%

A Methodology for Engineering Domain Ontology using Entity Relationship Model

Raza¹,

Rahmah²,

Raza³

et al. 2019

IJACSA

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Ontology engineering is an important aspect of semantic web vision to attain the meaningful representation of data. Although various techniques exist for the creation of ontology, most of the methods involve the number of complex phases, scenario-dependent ontology development, and poor validation of ontology. This research work presents a lightweight approach to build domain ontology using Entity Relationship (ER) model. Firstly, a detailed analysis of intended domain is performed to develop the ER model. In the next phase, ER to ontology (EROnt) conversion rules are outlined, and finally the system prototype is developed to construct the ontology. The proposed approach investigates the domain of information technology curriculum for the successful interpretation of concepts, attributes, relationships of concepts and constraints among the concepts of the ontology. The experts' evaluation of accurate identification of ontology vocabulary shows that the method performed well on curriculum data with 95.75% average precision and 90.75% average recall.

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Section: Introductionmentioning

confidence: 99%

A Methodology for Engineering Domain Ontology using Entity Relationship Model

Raza¹,

Rahmah²,

Raza³

et al. 2019

IJACSA

Self Cite

View full text Add to dashboard Cite

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“…Our approach extends the model presented in [3] via disambiguation of query term sense and semantic similarity strategy for selecting and ranking expanded terms.…”

Section: Introductionmentioning

confidence: 99%

Sensual Semantic Analysis for Effective Query Expansion

Raza¹,

Rahmah²,

Noraziah³

et al. 2018

ijacsa

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The information has evolved rapidly over the World Wide Web in the past few years. To satisfy information needs, users mostly submit a query via traditional search engines, which retrieve results on the basis of keyword matching principle. However, a keyword-based search cannot recognize the meanings of keywords and the semantic relationship among the terms in the user's query; thus, this technique cannot retrieve satisfactory results. The expansion of an initial query with relevant meaningful terms can solve this issue and enhance information retrieval. Generally, query expansion methods consider concepts that are semantically related to query terms within the ontology as candidates in expanding the initial query. An analysis of the correct sense of query terms, rather than only considering semantic relations, is necessary to overcome language ambiguity problems. In this work, we proposed a query expansion framework on the basis of query sense analysis and semantics mining using computer science domain ontology, followed by working prototype of the system. The experts analyzed the results of system prototype over test dataset and Web data, and found a remarkable improvement in the overall search performance. Furthermore, the proposed framework demonstrated better mean average precision and recall values than the baseline method.

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Influence of Network Speed on Structured Query Language (SQL) Database Data Transmission Performance in an Internet of Things (IoT) Sensing Device on Single Board Computers (SBC)

Azhar¹,

Hasna²,

Roslina³

et al. 2019

IOP Conf. Ser.: Mater. Sci. Eng.

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One of the crucial elements in an Internet of Things (IoT) environment is a database. IoT performance will be at stake if the wrong database is adopted. In this research, three Structured Query Language (SQL) databases were tested against multiple network speeds in an IoT device. Single board computers (SBC) were used as a media of testing instead of an ordinary computer. A controlled wireless sensor network (WSN) was developed with several uniform constants and variable network speeds. A new data transmission rate equation also was proposed and tested. From the result, it was found that not all SQL databases can cater IoT devices. Some of them showed that performance decreased along with network speed. The correlation, between 0.90 and 0.96, proved the strong influence between the research subjects. In addition, file-type database is the best option available for SQL-wise IoT storage.

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Query Expansion Using Conceptual Knowledge in Computer Science

Cited by 4 publications

References 0 publications

A Methodology for Engineering Domain Ontology using Entity Relationship Model

A Methodology for Engineering Domain Ontology using Entity Relationship Model

Sensual Semantic Analysis for Effective Query Expansion

Influence of Network Speed on Structured Query Language (SQL) Database Data Transmission Performance in an Internet of Things (IoT) Sensing Device on Single Board Computers (SBC)

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