Multidimensional concept extraction and validation from OLAP requirements in NL

Bargui, Fahmi; Ben-Abdallah, Hanêne; Feki, Jamel

doi:10.1109/nlpke.2009.5313769

Cited by 5 publications

(5 citation statements)

References 3 publications

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“…For their part [15], suggested specifying requirements using a template that embodies the concepts of a decision-making process and provided a linguistic framework for acquiring analytical queries. This proposed framework simplifies the automated analysis of queries without overly constricting writing styles.…”

Section: Relate Workmentioning

confidence: 99%

Knowledge Extraction from the Language Extended Lexicon Glossary Using Natural Language Processing

Antonelli,

Lezoche,

Delle Ville

2024

TecnoL.

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Successful software development requires good specifications, that is, correct, consistent, and unambiguous requirements. Natural language artifacts are the most used tools for writing specifications; nevertheless, the use of natural language can introduce many defects such as ambiguity, vagueness, and generality. In light of this, the purpose of this paper is to propose an approach for writing good specifications and extracting knowledge from them. The proposed approach uses a particular lexicon, the Language Extended Lexicon (LEL) glossary, and suggests rules for extracting knowledge (concepts, attributes, and relationships) from it. This paper also presents a prototype that implements and supports the proposed approach, as well as a preliminary evaluation of the approach. In conclusion, the proposed approach represents a theoretical contribution, which was evaluated using the System Usability Scale, and its evaluation results are promising, as it obtained the maximum score.

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Section: Relate Workmentioning

confidence: 99%

Knowledge Extraction from the Language Extended Lexicon Glossary Using Natural Language Processing

Antonelli,

Lezoche,

Delle Ville

2024

TecnoL.

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“…which can be regarded as a query-driven approach since it starts from naturallanguage descriptions of the end-users analyses. NLP is also used in [27], where OLAP requirements are expressed in natural language via a specification template to be then used for deriving multidimensional schemata; to ensure the quality of the result, they use a data dictionary to remove ambiguities and resolve conflicts.…”

Section: Multidimensional Modelingmentioning

confidence: 99%

“…This section introduces the rules used to derive multidimensional elements from a LEL in order to create one or more draft schemata. These rules, summarized in Table 3, provide a synthesis of different approaches to multidimensional modeling [26][27][28][50][51][52][53]; they analyze symbols and their notions to derive different multidimensional elements: facts, measures, dimensions, etc.…”

Section: Derivation Rulesmentioning

confidence: 99%

“…These categorization is used by the rules proposed in order to identify elements and relationships [28,51]. Rules may also take into account some specific syntax and semantics expressed in the notion (e.g., Rule 4 relies on the identification of aggregation semantics to identify levels [27]). The description of each rule is complemented with examples based on the car selling business and with a short justification.…”

Section: Expressions Of Possibility In Objects and Subjects Determine...mentioning

confidence: 99%

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Multidimensional modeling driven from a domain language

2022

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The multidimensional model is based on the concepts of facts (business phenomena to be analyzed), dimensions (coordinates for analyzing a fact), hierarchies (descriptions of each dimension at progressively coarser levels of aggregation), and measures (numerical attributes that quantify a fact), and it is commonly adopted for representing data to support the decision-making process. Though multidimensional modeling has been widely investigated, requirements elicitation is still an open issue mainly due to the poor knowledge end-users have of the multidimensional model on the one hand, to the lack of a domain language shared with designers on the other. In the direction of bridging this gap, this paper proposes an approach to obtain a multidimensional schema from the language of the domain captured through a Language Extended Lexicon (LEL). LELs have been introduced as structured glossaries to describe the language used in the application domain, aimed at facilitating requirements elicitation in software engineering. Methods: Our approach consists of two steps. In the first one, end-users apply a set of derivation rules to the LEL in order to obtain draft multidimensional schemata. The second step relies on Multidimensional Modeling Driven From a Domain Language the interaction of end-users and designers to review and edit these draft multidimensional schemata so as to obtain the final ones. Results: The approach is validated via an experiment made on a case study, showing that end-users who apply our rules tend to produce multidimensional schemata that are more correct than those produced by end-users who work freely. Conclusion: Our rules provide a structured context where subjectivity has a smaller impact than in the case of designing with no guidelines, thus effectively supporting the collaboration between end-users and designers.

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“…Their approach automates the reasoning about the decision-ma king knowledge to overcome the lack of domain knowledge ontology and allows systematic requirements elicitation. In an attempt to involve the decision-makers, the authors in [13] define a NL-based template and a process for requirement validation. They defined three steps to remove any confusion in the NL queries : i) Syntax checking and Part of Speech (PoS) tagging, ii) Mapping and disambiguation, and iii) Generation and verification.…”

Section: IIImentioning

confidence: 99%

A Prototyped NL-Based Approach for the Design of Multidimensional Data Warehouse

Alzahrani

Alqarni

Feki

2020

IJCIT

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Organizations are more and more interested in the Data Warehouse (DW) technology and data analytics to base their decision-making processes on scientific arguments instead of intuition. Despite the efforts invested, the DW design issue remains a great challenging research domain. The design quality of the DW depends on several aspects, as the requirement gathering. In this context, we propose a Natural Language (NL) based design approach, which is twofold, first, it facilitates the involvement of the decision-makers in the DW design process; indeed, NL can encourage the decision-makers to express their requirements as English-like sentences conform to NL-templates. Secondly, our approach aims to generate semi-automatically a DW schema from a set of requirements gathered as analytical queries compliant to the NL-templates. This design approach relies on (i) two easy-to-use NL-templates to specifying the analysis components, and (ii) a set of five heuristic rules for extracting the multidimensional concepts from the requirements. We demonstrate the feasibility of our approach by developing the prototype Natural Language Decisional Requirements to DW Schema (NLDR2DWS).

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Multidimensional concept extraction and validation from OLAP requirements in NL

Cited by 5 publications

References 3 publications

Knowledge Extraction from the Language Extended Lexicon Glossary Using Natural Language Processing

Knowledge Extraction from the Language Extended Lexicon Glossary Using Natural Language Processing

Multidimensional modeling driven from a domain language

A Prototyped NL-Based Approach for the Design of Multidimensional Data Warehouse

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