Muhammad Taimoor Khan

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Lifelong machine learning (LML) models learn with experience maintaining a knowledge-base, without user intervention. Unlike traditional single-domain models they can easily scale up to explore big data. The existing LML models have high data dependency, consume more resources, and do not support streaming data. This paper proposes online LML model (OAMC)(More)
Huge volume of content is produced on multiple online sources every day. It is not possible for a user to go through these articles and read about topics of interest. Secondly professional articles, blog and forum have many topics discussed in a single discussion. Automatic knowledge-based topic models is a recent approach in Natural Language Processing(More)
Topic models are extensively used for text analysis to extract prominent concepts as topics in a large collection of documents about a subject domain. They are extended with different approaches to suit various application areas. Automatic knowledge-based topic models are recently introduced to specifically meet the processing needs of large-scale data(More)
The user generated data on social online platforms is a very resourceful medium for building applications. It provide an easy, cheap and efficient way to address the opinions expressed by millions of users. There are various commercial applications developed that analyze the products based on user reviews. However, no considerable research work is carried(More)
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