Formal context reduction in deriving concept hierarchies from corpora using adaptive evolutionary clustering algorithm star

It is beneficial to automate the process of deriving concept hierarchies from corpora since a manual construction of concept hierarchies is typically a time-consuming and resource-intensive process. As such, the overall process of learning concept hierarchies from corpora encompasses a set of steps: parsing the text into sentences, splitting the sentences and then tokenising it. After the lemmatisation step, the pairs are extracted using formal context analysis (FCA). However, there might be some uninteresting and erroneous pairs in the formal context. Generating formal context may lead to a time-consuming process, so formal context size reduction is require to remove uninterested and erroneous pairs, taking less time to extract the concept lattice and concept hierarchies accordingly. In this premise, this study aims to propose two frameworks: (1) A framework to review the current process of deriving concept hierarchies from corpus utilising formal concept analysis (FCA); (2) A framework to decrease the formal context’s ambiguity of the first framework using an adaptive version of evolutionary clustering algorithm (ECA*). Experiments are conducted by applying 385 sample corpora from Wikipedia on the two frameworks to examine the reducing size of formal context, which leads to yield concept lattice and concept hierarchy. The resulting lattice of formal context is evaluated to the standard one using concept lattice-invariants. Accordingly, the homomorphic between the two lattices preserves the quality of resulting concept hierarchies by 89% in contrast to the basic ones, and the reduced concept lattice inherits the structural relation of the standard one. The adaptive ECA* is examined against its four counterpart baseline algorithms (Fuzzy K-means, JBOS approach, AddIntent algorithm, and FastAddExtent) to measure the execution time on random datasets with different densities (fill ratios). The results show that adaptive ECA* performs concept lattice faster than other mentioned competitive techniques in different fill ratios.

Hierarchy of Values in Qur’anic Hermeneutic of Abdullah Saeed (A Study of Contextual Interpretation in Q.S. Al-Hujurat)

This article discusses an interpretation of the Qur’an by Abdullah Said using the contextual interpretation model. However, this paper will focus on how Abdullah Saeed developed the concept hierarchy of values inspired by Fazlur Rahman's thought, how application and implication of this concept in Qur’anic interpretation. Abdullah Saeed developed and formulated the concept hierarchy of values into five levels, including obligatory values, fundamental values, protective values, implementational values, and instructional values. The five hierarchies of values become a complete unified frame as an effort to the contextual interpretation of the Qur’an, especially the ethico-legal verses that mostly fill the daily life of most Muslims based on the understanding of maqashid al-sharia and the concept of good deeds. This study uses a descriptive analysis method and hermeneutic analysis techniques to apply the concept hierarchy of values in the Qur’anic interpretation. The results of this paper are in the contextual interpretation of QS. Al-Hujurat in the 1st-5th verses are instructional value; the 6th and 9th verses are combination of fundamental, protectional and impementational values; the 7th-8th verses and the 14th-18th verses are obligatory value; the 10th verse implementational value; the 11th-13th verses are instructional value. In QS. Al-Hujurat contain the five hierarchical levels of values that have been specifically conceived by Abdullah Saeed

Toward Islamic Psychology: Understanding of Mental Illness from Qur'anic Verses

This article discusses an interpretation of the Qur’an by Abdullah Saeed using the contextual interpretation model. However, this paper will focus on how Abdullah Saeed developed the concept of the hierarchy of values inspired by Fazlur Rahman's thought, which discussed the problem hierarchy of values as general principles. However, Fazlur Rahman did not provide specific devices to develop the hierarchy of values. Abdullah Saeed developed and formulated the concept hierarchy of values into five levels, including obligatory values, fundamental values, protective values, implementational values, and instructional values. The five hierarchies of values become a complete unified frame as an effort to the contextual interpretation of the Qur’an, especially the ethico-legal verses that mostly fill the daily life of most Muslims based on the understanding of maqashid al-sharia and the concept of good deeds. This study uses a descriptive analysis method and hermeneutic analysis techniques to apply the concept hierarchy of values in the Qur’anic interpretation. The results of this paper are in the contextual interpretation of QS. Al-Hujurat verses 1-18 contain the five hierarchical levels of values that have been specifically conceived by Abdullah Saeed

Meta heuristic feature optimization for ontology-based data security in a campus workplace with robotic assistance

BACKGROUND: For campus workplace secure text mining, robotic assistance with feature optimization is essential. The space model of the vector is usually used to represent texts. Besides, there are still two drawbacks to this basic approach: the curse and lack of semantic knowledge. OBJECTIVES: This paper proposes a new Meta-Heuristic Feature Optimization (MHFO) method for data security in the campus workplace with robotic assistance. Firstly, the terms of the space vector model have been mapped to the concepts of data protection ontology, which statistically calculate conceptual frequency weights by term various weights. Furthermore, according to the designs of data protection ontology, the weight of theoretical identification is allocated. The dimensionality of functional areas is reduced significantly by combining standard frequency weights and weights based on data protection ontology. In addition, semantic knowledge is integrated into this process. RESULTS: The results show that the development of the characteristics of this process significantly improves campus workplace secure text mining. CONCLUSION: The experimental results show that the development of the features of the concept hierarchy structure process significantly enhances data security of campus workplace text mining with robotic assistance.

Exploratory Navigation and Selective Reading

Navigating a collection of documents can be facilitated by obtaining a human-understandable concept hierarchy with links to the content. This is a non-trivial task for two reasons. First, defining concepts that are understandable by an average consumer and yet meaningful for a large variety of corpora is hard. Second, creating semantically meaningful yet intuitive hierarchical representation is hard, and can be task dependent. We present out system Navigation.ai which automatically processes a document collection, induces a concept hierarchy using Wikipedia and presents an interactive interface that helps user navigate to individual paragraphs using concepts.

Enhancing User Profile Accuracy for Personalized Web Systems

Personalized Web Applications aim to improve the user's browsing experience by offering customized products and services based on his preferences and needs. A key feature of a successful personalization system is building profiles that accurately express the real interests and needs of each user. In this work, we focus on creating accurate, complete and dynamic profiles by capturing and tracking the users’ browsing activities. Moreover, we implement techniques to increase the accuracy of the retrieved user profiles by collecting more browsing data, identifying the most important concepts and removing irrelevant ones, and the number of levels from the concept hierarchy in the reference ontology that we should use to efficiently represent the users’ reel interests and needs. The result is a complete, dynamic, and accurate user profile that can be used to give users better-personalized browsing experience.

PENGEMBANGAN LEMBAR KEGIATAN PESERTA DIDIK BERBASIS HIERARKI KONSEP POKOK BAHASAN HIDROLISIS GARAM

This research is a research design to obtain a product prototype teaching material Student Activity Sheet (LKPD). LKPD to be designed and developed is the Concept Hierarchy Based LKPD for Salt Hydrolysis Subjects. The research method used was the research development of Sivasailam Thiagarajan et al. 4-D development model: Define, Design, Develop and Disseminate. Define stage/formulate student needs and synchronize the indicators/competencies that students want to achieve in understanding the HG material. The Design Stage is a designation of LKPD which has considered the inclusion of all BHK-based pursuit objective indicators contained in LKPD. The final result of the Design stage is the final draft of the LKPD (prototype) which must be validated which is carried out at the Develop stage. LKPD validation by three experts who assessed the feasibility aspects of content, linguistics, presentation and graphics, respectively scored 89.28%, 91.67%, 93.75% and 87.50% with valid categories. After LKPD was declared valid, LKPD was tested on high school students to see the responses and input from the teacher in the field of chemistry studies. Response of 20 students rated positive/useful with a score of 91.07% in the very positive category and assessed its practicality by two teachers and got the response results with a percentage of 93.75% with a very practical category.