Semantic web and its technologies have been eyed in many fields. They have the capacity to organize and link data over the web in a consistent and coherent way. Semantic web technologies consist of RDF schema, OWL, and rule and query languages like SPARQL and these technologies will help the various domains to resolve their problems. This review paper starts with analyzing the nature of semantic web and its requirements. We have considered all 10 domains which are closely related to semantic web and its technologies. For a better understanding of the paper, we have separated it into three major contributions. First, we analyze semantic web and those domains that increase the growth of the semantic web. Second, we discuss all domains where semantic web technologies play a vital role. Third, we emphasize those domains that go hand in hand with semantic web technologies. This review paper will be utilized as an unbiased direction for the researchers.

In this era of web, we have a huge amount of information overloaded over Internet. It becomes a herculean task for the user to get the relevant information. To some extent, the problem is being solved by the search engines, but they do not provide the personalization of data. So, to further filter the information, we need a recommendation engine. In this paper, we have described the various web recommender systems in use by some popular web sites on the internet like Amazon.com, LinkedIn.com, and YouTube.com etc. Further, we have described the various approaches used in the various recommender systems such as Content based, Collaborative and Hybrid recommender system. At the end of this paper, we focus on some of the main challenges faced by the web recommender systems and analyze some techniques to overcome them.

The world is witnessing an increasing use of IoT-based devices to collect sensor data in order to perceive the real world and generate abstractions. This data is highly heterogeneous in nature as it is obtained from various domains utilizing different representation schemes. Semantic approaches come as a rescue to this interoperability problem incurred because of heterogeneous sensor data from IoT devices. The data thus obtained should be represented in form of ontologies which are considered as the cornerstone of the Semantic Web for knowledge sharing, information extraction, information integration and many more. The content and the quality of the ontologies should be analyzed by evaluating them to ensure that the ontology is well designed, structured, and contains all essential concepts and relationships between them for efficient reasoning. This paper focuses on the evaluation of ontologies and, as a case study, evaluates a Military Resource Ontology (MRO) by using evaluation tools such as OntoMetric, OOPs!, ONTOCOM, based on evaluation approaches, aspects and criteria. These tools detect errors by diagnosing various metrics and pitfalls. Evaluation methods are grouped in two phases: verification and validation. In this paper, ‘QueryOnto’ tool is introduced to verify and validate the MRO by searching, query/answering, and visualizing.