Heritage allows us to learn about the different monuments of importance and the inherited traditions from our ancestors. However, many times the monuments get partly ruined due to natural wear and tear, sometimes due to attacks by invaders. To preserve the cultural heritage virtually, many researchers have used augmented, virtual and mixed reality for bringing ancient environments to live in those heritage sites. This study aims to identify publications related to virtual, augmented and mixed reality in cultural heritage and to present the bibliometric analysis of these studies. The research articles on virtual, augmented, and mixed reality in cultural heritage are retrieved using the Scopus database. The analysis is performed using VOSviewer and various parameters such as bibliographic coupling of the countries, publications, journals, authors, and cooccurrences of the author keywords are performed. From the analysis done in this study, it is discovered that the augmented, virtual and mixed reality research in the domain of cultural heritage is mostly concentrated in Italy and surrounding European countries. However, it is also found that the research in this domain is lagging in many countries even if those countries are the homes of various heritage sites. This study provides an extensive analysis of the recent literature related to augmented, virtual and mixed reality research in cultural heritage. This information science based analysis will help researchers to identify the prominent journals in this domain, recognize stalwarts in this field and follow their works, find out path-breaking publications to refer to, and predict the direction of future studies.

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All of us are aware of how important knowledge is and it is also true that mostly the data or knowledge is in the form of books or online articles, or various pdfs i.e. in text format. But not all of us are privileged to read. Some are illiterate, some are blind, and some have reading difficulties. Hence, a form of adaptive technology or procedure that reads digital text aloud, which is called text-to-speech (TTS) was developed. It is occasionally referred to as "read-aloud" technology. Words on a computer or other digital device can be converted into audio using TTS. TTS is particularly beneficial for all those people who have reading difficulties or are illiterate. Also, a significant amount of research has been done and is currently being done on text-to-speech technology. Various technologies, methodologies, and algorithms are used in the various proposed approaches and solutions for TTS. This research presents a systematic review of all those methods which have been proposed and implemented by different active researchers in this field.

Nowadays, E-commerce websites has become a vital part of regular life. The pandemic has taken a quick step towards the digital world and initiated changes in online shopping behaviors. While buying products online many people read the reviews related to the product and then decide on buying it. So, reviews play an important role if a customer wants to buy any product. This leads to increased spam review volume in social networks and e-commerce websites like Flipkart, Amazon, etc. Fake reviews can be used to demote a good product or to promote a bad product, so there is a need for robust and reliable techniques to detect fake reviews which can be beneficial to the customer as well as to the vendor. The objective of this survey paper is to get an overview of different methodologies used to solve such problems. This research presents a systematic review on methods to detect spam review using different Deep Learning (DL) Approaches, Machine Learning (ML) Methods, Natural Language Processing (NLP), and Sentiment Analysis.