Outlier detection aims to reveal data patterns different from existing data. Benefit from its
good robustness and interpretability, the outlier detection method for numerical dataset …

Keyword extraction is a major step to extract plenty of valuable and meaningful information
from the rich source of World Wide Web (WWW). Different keyword extraction algorithms are …

two keyword-extraction ways are usually used, one is simply using the information from
exactly single word like word frequency and TF. IDF, the other is based on the relationship …

The proposed methodology employs a novel statistical integrated graph-based sentence
sensitivity ranking algorithm for text document clustering. Clustering of documents is a task …

Obtaining the most representative set of words in a document is a very significant task, since
it allows characterizing the document and simplifies search and classification activities. This …

The proposed methodology employs Harris hawks optimizer algorithm for text document
clustering. The main influence of Harris hawks optimizer algorithm is the collective character …

Sažetak The area of information retrieval (IR) has taken on increasing importance in recent
years. This field is now of interest to large communities in several application domains …

Keyphrase extraction is one of fundamental natural language processing (NLP) tools to
improve many text-mining applications such as document summarization and clustering. In …

Due to the increasing adoption of Information Technology (IT) and its significant impact on
individual learning preferences, there is a compelling need to enhance Social Learning …

The co-word extraction method using a statistical integrated graph based approach has
been adopted, and the purpose of this work is to extract the most important cowords from the …