Knowledge-Based Semantic Information Indexing and Management Framework: Integration of Structured Knowledge and Information Management Systems*
محل انتشار: مجله مهندسی کامپیوتر و دانش، دوره: 3، شماره: 2
سال انتشار: 1400
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 129
فایل این مقاله در 20 صفحه با فرمت PDF قابل دریافت می باشد
- صدور گواهی نمایه سازی
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_CKE-3-2_001
تاریخ نمایه سازی: 25 خرداد 1401
چکیده مقاله:
One of the most challenging aspects of developing information systems is the processing and management of large volumes of information. One way to overcome this problem is to implement efficient data indexing and classification systems. As large volumes of generated data comprise of non-structured textual data, developing text processing, management and indexing frameworks can play an important role in providing users with accurate information according to their preferences. In this paper, a novel method of semantic information processing, management and indexing is introduced. The main goals of this study is to integrate structured knowledge of ontology and Knowledge Bases (KBs) in the core components of the method, to enrich the contents of the documents, to have multi-level semantic network representation of textual resources, to introduce a hybrid weighting schema (salient score) and finally to propose a hybrid method of semantic similarity computation. The structured knowledge of ontology and KBs are integrated from all aspects of the proposed method. The obtained results indicate the accuracy and optimal performance of the proposed framework. The obtained results suggest that using knowledge-based models leads to higher performance and accuracy in identifying and classifying documents according to user preferences; however, if learning-based models are not provided with sufficient amount of training data, they cannot yield satisfying results. The results also demonstrate that the complete integration of ontology and KBs in information systems can significantly contribute to a better representation of documents and evidently superior functionality of information processing, management and indexing systems.
کلیدواژه ها:
نویسندگان
Morteza Jaderyan
Department of Computer Engineering, Bu-Ali Sina University, Hamedan, Iran.
Hassan Khotanlou
Department of Computer Engineering, Bu-Ali Sina University, Hamedan, Iran.
مراجع و منابع این مقاله:
لیست زیر مراجع و منابع استفاده شده در این مقاله را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود مقاله لینک شده اند :