Sentiment analysis, also known as opinion mining, grows out of this need. This paper first gives an overview of deep learning and then provides a comprehensive survey of its current applications in sentiment analysis. Opinion Mining and Sentiment Analysis: A Survey . What Were The Results Of The Study? However, sentiment is a view colored by an emotion. Opinion mining: The basics. Book: Sentiment Analysis and Opinion Mining (Introduction and Survey), Morgan & Claypool, May 2012. All text is inherently minable. This book focuses on the basic concepts and the related technologies of data mining for social medial. Companies use sentiment analysis for understanding public opinion, performing market research, analyzing brand reputation, recognizing customer … All text is inherently minable. One opinion from a single person is usually A Survey of Opinion Mining and Sentiment Analysis 7 not sufficient for action. The Handbook of Natural Language Processing, Second Edition presents practical tools and techniques for implementing natural language processing in computer systems. This survey paper tackles a comprehensive overview of the last update in this field. This paper represents the survey of different sentiment analysis methods. They are trying to fetch opinion information and analyze it automatically with computers. This represents that there occurs a need Keywords: Social Media, Twitter, Sentiment analysis, Opinion mining, Sentiment Polarity, Machine learning. The basic in opinion mining is classifying the polarity of text in terms of positive (good), negative (bad) or neutral (surprise). Text Mining and Sentiment Analysis: Analysis with R. This is the third article of the “Text Mining and Sentiment Analysis” Series. Opinion Mining and Sentiment Analysis on a Twitter Data Stream BalakrishnanGokulakrishnan * 1, ... Abstract - Opinion mmmg and sentiment analysis is a fast growing topic with various world applications, from polls to ... Survey applications It is also known as opinion mining, mood extraction and emotion analysis. Found insideThis book includes a selection of papers from the 2017 International Conference on Software Process Improvement (CIMPS’17), presenting trends and applications in software engineering. Okoro Jennifer Chimaobiya Mrs. Hari Priya. Sentiment analysis from text consists of extracting information about opinions, sentiments, and even emo-tions conveyed by writers towards topics of interest. opinion mining (sentiment mining): Opinion mining is a type of natural language processing for tracking the mood of the public about a particular product. To facilitate future work, a discussion of available resources, benchmark datasets, and evaluation campaigns is also provided. 1. Opinion mining can be used in many new applications. It also represents the features and limitations of different sentiment polarity techniques. How toacquire the public hotspots and trends by collecting and analyzing the massive data on the Internetis an important research topic in public opinion analysis. Tsytsarau and Palpanas presented a survey on SA by focusing on opinion mining, opinion aggregation including spam detection and contradiction analysis. ... Opinion mining and sentiment analysis for Arabic on-line … sales of the product has led to study of the field opinion mining and sentiment analysis. In this book common sense computing techniques are further developed and applied to bridge the semantic gap between word-level natural language data and the concept-level opinions conveyed by these. A brief survey has been done on the techniques used for sentiment analysis. A Survey on Analysis of Twitter Opinion Mining Using Sentiment Analysis Anusha K S1 , Radhika A D2 1M Tech, CSE Dept. Sentiment analysis, also termed as opinion mining, is an application of natural language processing, computational linguistics, and content interpretation that, by analyzing the viewpoint, recognizes and retrieves emotion polarity from the content. Opinion Mining and Sentiment Analysis is the first such comprehensive survey of this vibrant and important research area and will be of interest to anyone with an interest in opinion-oriented information-seeking systems. in sentiment analysis in recent years. Chapter 7. Employee sentiment analysis is the use of natural language processing (NLP) and other AI techniques to automatically analyze employee feedback and other unstructured data to quantify and describe how employees feel about their organization. Sentiment is a thought, attitude or judgment provoked by a feeling. Scores closer to 1 indicate a higher confidence in the label's classification, while lower scores indicate lower confidence. The task is … Sentiment Analysis can be performed using two approaches: Rule-based, Machine Learning based. Bangalor-560069, India. Found insideThis book constitutes the refereed proceedings of the 9th Mexican Conference on Pattern Recognition, MCPR 2017, held in Huatulco, Mexico, in June 2017. Found insideThis book brings together scientists, researchers, practitioners, and students from academia and industry to present recent and ongoing research activities concerning the latest advances, techniques, and applications of natural language ... Sentiment analysis (SA) also known as opinion mining is a sub-division of data mining. SA refers to the practice of applying text analysis and natural language processing (NLP) for the purpose of identifying, extracting, and analyzing subjective information from textual sources. In the broadest terms, opinion mining is the science of using text analysis to understand the drivers of public sentiment. . Twitter sentiment or opinion expressed through it may be positive, negative or neutral. SA is the computational treatment of opinions, sentiments and subjectivity of text. Found inside – Page iThis two-volume set (CCIS 905 and CCIS 906) constitutes the refereed proceedings of the Second International Conference on Advances in Computing and Data Sciences, ICACDS 2018, held in Dehradun, India, in April 2018. To facilitate future work, a discussion of available resources, benchmark datasets, and evaluation campaigns is also provided. 1. Artificial Intelligence Review, 52(3), 1495–1545. Liu presented different tasks possible and works published in SA and opinion mining. Although linguistics and natural language processing (NLP) have a long history, little research had been done about people’s opinions and sentiments before the year 2000. It is one of the most active research areas in natural language processing and is also widely studied in data mining, Web mining, and text mining. This survey covering published literature during 2002–2015, is organized on the basis of sub-tasks to be performed, machine learning and natural language processing techniques used and applications of sentiment analysis. Sentiment Analysis v3.1 can return response objects for both Sentiment Analysis and Opinion Mining. OM and Sentiment Analysis tool ―process a set of search results for a given item, generating product attributes (quality, features etc.) Index Terms- NBA, Opinion Mining, Sentiment Analysis… The current research is focusing on the area of Opinion Mining also called as sentiment analysis due to sheer volume of opinion rich web resources such as discussion forums, review sites and blogs are available in digital form. from the text and audio, video data. Sentiment analysis is a process of analyzing, processing, concluding, and inferencing subjective texts with the sentiment. Introduction A Sentiment analysis and opinion mining are subfields of machine learning. This book constitutes the refereed proceedings of the First International Conference on Advanced Machine Learning Technologies and Applications, AMLTA 2012, held in Cairo, Egypt, in December 2012. They are very important in the current scenario because, lots … A Survey on Analysis of Twitter Opinion Mining Using Sentiment Analysis Anusha K S1 , Radhika A D2 1M Tech, CSE Dept. In general, opinion mining helps to collect information about the positive and negative aspects of a particular topic. Due to the sheer volume of opinion rich web resources such as discussion forum, review sites , blogs and news corpora available in digital form, much of the current research is focusing on the area of sentiment analysis. Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language. New Book: Sentiment Analysis: mining opinions, sentiments, and emotions. Opinion Mining. Machine Learning (ML) based sentiment analysis. Opinion refers to ext raction of lines in raw data which expresses an opinion. The major challenge of the area of Sentiment analysis and Opinion mining lies in identifying the emotions expressed in these texts. INTRODUCTION In this book, the authors propose an overview of the main issues and challenges associated with current sentiment analysis research and provide some insights on practical tools and techniques that can be exploited to both advance the state ... Found insideThis book presents interdisciplinary research on cognition, mind and behavior from an information processing perspective. A Survey On Classification Techniques For Opinion Mining And Sentiment Analysis. A Survey of Opinion Mining and Sentiment Analysis. This paper first gives an overview of deep learning and then provides a comprehensive survey of its current applications in sentiment analysis. Introduction A Sentiment analysis and opinion mining are subfields of machine learning. The rare survey papers that have been published focusing on a particular aspect (for example, the sentiment classification techniques, the challenges and application of opinion mining and sentiment analysis, etc.) Abstract—Sentiment Analysis (SA), an application of Natural Language processing (NLP), has been witnessed a blooming interest over the past decade.It is also known as opinion mining, mood extraction and emotion analysis. Identifying and categorizing opinions expressed in a piece of text, especially in order to determine whether the writer's attitude towards a particular topic, product, etc. b0005 B. Pang, L. Lee, Opinion mining and sentiment analysis, Found. mining and sentiment analysis. They are trying to fetch opinion information and analyze it automatically with computers. Sentiment Analysis (SA) is an ongoing field of research in text mining field. Data Analytics is widely used in many industries and organization to make a better Business decision. opinion mining and sentiment analysis, which deals with the computational treatment of opinion, sentiment, and subjectivity in text, has thus occurred at least in part as a direct response to the surge of interest in new systems that deal directly with opinions as a first-class object. Sentiment Analysis (SA) and Opinion Mining (OM) are subfields of machine learning. Found inside – Page iHighlighting a range of topics such as data mining, digital evidence, and fraud investigation, this book is ideal for security analysts, IT specialists, software engineers, researchers, security professionals, criminal science professionals ... Many recently proposed algorithms' enhancements and various SA applications are investigated and presented briefly in this… issues. The basic idea is to find the polarity of the text and classify it into positive, negative or neutral. Sentiment analysis returns a sentiment label and confidence score for the entire document, and each sentence within it. different articles that solve a general Sentiment Analysis downside are classified offer contribution within the … Sentiment Analysis is a technique used in text mining. This situation is producing increasing interest in methods for automatically extracting and analyzing individual opinion from web documents such as customer reviews, weblogs and comments on news. In this survey of opinion mining An opinion has 3 main BR class may be classified to lexica, Corpora or dictionaries. Sentiment analysis (or opinion mining) may be a natural processing technique want to determine whether data is positive, negative, or neutral. This new research domain is usually called Opinion Mining and Sentiment Analysis. Found insideFurther, this volume: Takes an interdisciplinary approach from a number of computing domains, including natural language processing, machine learning, big data, and statistical methodologies Provides insights into opinion spamming, ... It is often equated to opinion mining, but it should also encompass emotion mining. Until now, researchers have developed several … ICoAC 2016 is an international conference in the field of Computer Science and Communication, focusing to address issues and developments in advanced computing The conference seeks to bring together international researchers to present ... KEYWORDS Sentiment Mining, Social Media Behaviour, Behaviour Prediction, Opinion Mining, Sentiments 1. In general, sentiment analysis tries to determine the sentiment … [8]. 5, no. Opinion refers to extraction of lines in raw data which expresses an opinion. Current-day opinion mining and sentiment analysis is a field of study at the crossroad of information retrieval and natural language processing and shares some characteristics with other disciplines such as text mining and information extraction.This paper try to cover some techniques and approaches that be used in this area. 1. Found insideAlthough AI is changing the world for the better in many applications, it also comes with its challenges. This book encompasses many applications as well as new techniques, challenges, and opportunities in this fascinating area. International Conference on Internet of Things and Machine Learning Oct 17, 2017-Oct 18, 2017 Liverpool, United Kingdom. Found insideThis book features selected research papers presented at the First International Conference on Computing, Communications, and Cyber-Security (IC4S 2019), organized by Northwest Group of Institutions, Punjab, India, Southern Federal ... In gener-al, sentiment analysis tries to determine the sentiment of a writer about some aspect or the overall contextual polarity of a docu-ment. It is also commendable that the book gives a balanced treatment of both ... in sentiment, opinion, and emotion expressions, which is the pair of sentiment and its target. It is a challenging natural language processing or text-mining problem. Sentiment analysis or opinion mining is a computational study of the opinions, judgments, attitudes, and emotions of a person towards an entity, individual, issue, event, topic, and attributes. This literature survey is done to study the sentiment analysis problem in-depth and to familiarize with other works done on the subject. They are very important in the current scenario because, lots … Found insideThe book covers core areas of sentiment analysis and also includes related topics such as debate analysis, intention mining, and fake-opinion detection. Found insideThe volume involves studies devoted to key issues of sentiment analysis, sentiment models, and ontology engineering. The book is structured into three main parts. By applying analytics to the structured and unstructured data the enterprises brings a great change in their way of planning and decision making. Found inside – Page iFeaturing research on topics such as knowledge retrieval and knowledge updating, this book is ideally designed for business managers, academicians, business professionals, researchers, graduate-level students, and technology developers ... 1188953999. Opinion analysis is very interesting research topic in both extraction of information and discovery of knowledge. 34 papers with code • 0 benchmarks • 7 datasets. From multiple opinions it is difficult to draw a conclusion (positive/negative). classification, opinion mining, subjectivity analysis, review mining or appraisal extraction and in some cases polarity classification) deals with computational treatment of opinion, sentiment and subjectivity in text (Pang & Lee 2008) [12]. Some of the most popular opinion mining sentiment analysis applications are: Social media analysis. 367–71. This survey covers techniques and approaches that promise to directly enable opinion-oriented information-seeking systems. Our focus is on methods that seek to address the new challenges raised by sentiment-aware applications, as compared to those that are already present in more traditional fact-based analysis. This paper provides an overall survey about sentiment analysis or opinion mining 3. in sentiment analysis in recent years. Chapters 3–9 discuss the core sentiment analysis tasks (e.g., sentiment classification, aspect analysis, and opinion summarization) and their current solution methods. Note What Opinion Mining Is And How It’s Used In Information Retrieval. group guidelines. Recently, many researchers have focused on this area. Sentiment Analysis (also known as opinion mining or emotion AI) is a sub-field of NLP that measures the inclination of people’s opinions (Positive/Negative/Neutral) within the unstructured text. This paper presents a survey which covers a problem of sentiment analysis, techniques and Sentiment analysis (SA) also known as opinion mining is a sub-division of data mining. A survey of sentiment analysis techniques. Recently, many researchers have focused on this area. The major challenge of the area of Sentiment analysis and Opinion mining lies in identifying the emotions expressed in these texts. Product reviews, for example, are often composed of different opinions about different characteristics of a product, like Price , UX-UI , Integrations , Mobile Version , etc. To solve the Sentiment classification downside as SC. Aspect-based opinion mining is one among the thought-provoking research field which focuses on the extraction of vivacious aspects from opinionated texts and polarity value associated with these. Key words: Opinion extraction, Opinion mining, Sentiment analysis, Subjectivity mining, Text mining INTRODUCTION Research in automatic Subjectivity and Sentiment Analysis (SSA), as subtasks of Affective Computing and Natural Language Our focus is on methods that seek to address the new challenges raised by sentiment-aware applications, as compared to those that are already present in more traditional fact-based analysis. This paper contains all the aspect related to opinion mining in terms of its classification, various mining techniques that is prevailing in the study of this field. Sentiment Analysis, Opinion Mining, Web Content, Machine Learning. For example, sentiment analysis, opinion mining, and polarity classification, which are define below, are rummage-sale to discourse the same concept. Opinion Mining and Sentiment Analysis is the first such comprehensive survey of this vibrant and important research area and will be of interest to anyone with an interest in opinion-oriented information-seeking systems. “A Survey on Sentiment Analysis and Opinion Mining Techniques.” Journal of Emerging Technologies in Web Intelligence, vol. Found insideThis 2 volume-set of IFIP AICT 583 and 584 constitutes the refereed proceedings of the 16th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2020, held in Neos Marmaras, Greece, in June ... Cambridge University Press, 2015. Found insideThis latest volume in the series, Socio-Affective Computing, presents a set of novel approaches to analyze opinionated videos and to extract sentiments and emotions. This approach depends largely on the type of algorithm and the quality of the training data used. Found inside – Page iFeaturing emergent research and optimization techniques in the areas of opinion mining, text mining, and sentiment analysis, as well as their various applications, this book is an essential reference source for researchers and engineers ... INTRODUCTION Sentiment Analysis (SA) or Opinion Mining (OM) is the computational study of people‟s opinions, attitudes and emotions toward an entity [3]. This book contains a wide swath in topics across social networks & data mining. Each chapter contains a comprehensive survey including the key research content on the topic, and the future directions of research in the field. Further, this volume: Takes an interdisciplinary approach from a number of computing domains, including natural language processing, machine learning, big data, and statistical methodologies Provides insights into opinion spamming, ... Sentiment analysis or opinion mining is the computational study of people’s opinions, appraisals, attitudes, and emotions toward entities, individuals, issues, events, topics and their attributes. “sentiment analysis and opinion mining: A survey”, International journal of advanced research in computer science and software enginnering,283- 294, Volume 2,Issue 6, june 2012. Cataldo Musto, Giovanni Semeraro, Marco Polignano, “A comparison of Lexicon-based approaches for Sentiment Analysis … This paper presents a survey covering the techniques and methods in sentiment analysis and challenges appear in the field. This book constitutes the refereed proceedings of the 5th International Conference on HCI in Business, Government and Organizations, HCIBGO 2018, held as part of the 20th International Conference on Human-Computer Interaction, HCII 2018, in ... broad. Major tasks listed are subjectivity and sentiment … The major challenge lies in analyzing the sentiments and identifying emotions expressed in texts. The comprehensive analysis of the methods which are used on user behavior prediction is presented in this paper. and don't concern the research work proposed this last two years. Here, we train an ML model to recognize the sentiment based on the words and their order using a sentiment-labelled training set. of Computer Science and Engineering VVCE, Mysuru 2Assistant Professor, CSE Dept. As such, while social media may be an obvious source of current opinion, reviews, call center transcripts, web pages, online forums, and survey responses can all prove equally useful. 415-463. It is also known as emotion extraction or opinion mining. For this reason, when we need to make a decision we often seek out the opinions of others. This is true not only for individuals but also for organizations. This book is a comprehensive introductory and survey text. However, few survey papers have been published in this area. Abstract: Sentiment analysis is an application of natural language processing. Found inside – Page iThis book constitutes the refereed proceedings of the First International Conference on Smart Trends in Information Technology and Computer Communications, SmartCom 2016, held in Jaipur, India, in August 2016. [24] B. Liu and L. Zhang, "A Survey of Opinion Mining and Sentiment Analysis," C. C. Aggarwal and C. Zhai, Eds., ed: Springer US, 2012, pp. Sentiment Analysis: Mining Opinions, Sentiments, and Emotions Bing Liu ... comprehensive yet in-depth survey of references in sentiment analysis. Abstract—Sentiment Analysis (SA), an application of Natural Language processing (NLP), has been witnessed a blooming interest over the past decade. The sentiment Opinion mining offers a window into the thoughts and feelings of the public, allowing businesses to improve the customer experience, perform competitive research, and understand opinions. While highlighting relevant topics, including the differences between ontology-based opinion mining and feature-based opinion mining, this book is an ideal reference source for information technology professionals within research or ... The first article introduced Azure Cognitive Services and demonstrated the setup and use of Text Analytics APIs for extracting key Phrases & Sentiment … A survey on classification techniques for opinion mining and sentiment analysis: 2. They are very important in the current scenario because, lots of user opinionated texts are available in the web now. This type of sentiment analysis focuses on understanding the aspects or features that are being discussed in a given opinion. Found insideThis book constitutes the thoroughly refereed proceedings of the second International Symposium on Intelligent Systems Technologies and Applications (ISTA’16), held on September 21–24, 2016 in Jaipur, India. This comparison will provide a detailed information, pros and cons in the domain of sentiment and opinion mining. INTRODUCTION Sentiment analysis or opinion mining is the computational study of people’s opinions, sentiments, This is a very popular field of research in text mining. Along with the success of deep learning in many application domains, deep learning is also used in sentiment analysis in recent years. Sentiment analysis is an emerging area of research to extract the subjective information in source materials by applying Natural Language processing, Computational Linguistics and text analytics and classify the polarity of the opinion stated. A SURVEY OF OPINION MINING AND SENTIMENT ANALYSIS Bing Liu University of Illinois at Chicago Chicago, IL liub@cs.uic.edu Lei Zhang University of Illinois at Chicago Chicago, IL lzhang32@gmail.com Abstract Sentiment analysis or opinion mining is the computational study of peo-ple’s opinions, appraisals, attitudes, and emotions toward entities, in- Subjectivity classification, sentiment classification, review usefulness measurement, lexicon creation, opinion word and product aspect extraction, and various applications of opinion mining. These six dimensions refer to tasks to be accomplished for SA. Ontology can be useful in globalizing the measurement standard of sentiments Opinion mining or Sentiment analysis Opinion mining is a technique to detect and extract subjective information in text documents. Keywords: Opinion mining, sentiment analysis, sentiment lexicon, feature extraction, sentiment classification 1. INTRODUCTION Sentiment analysis or opinion mining is the computational study of people’s opinions, sentiments, Found inside – Page 265Liu, B.: Sentiment Analysis: Mining Opinions, Sentiments, and Emotions. Cambridge University Press (2015) 2. Ravi, K., Ravi, V.: A survey on opinion mining ... Found insideOngoing advancements in modern technology have led to significant developments in artificial intelligence. With the numerous applications available, it becomes imperative to conduct research and make further progress in this field. Opinion Mining a nd Sentimental Analysis A. Opinion quintuples defined above provide an ex- cellent source of information for generating both qualitative and quan- titative summaries. To solve the Sentiment classification downside as SC. Found insideThe book focuses on soft computing and its applications to solve real-world problems in different domains, ranging from medicine and health care, to supply chain management, image processing and cryptanalysis. Brand awareness. of Computer Science and Engineering VVCE, Mysuru 2Assistant Professor, CSE Dept. Found insideThe book presents new approaches and methods for solving real-world problems. Opinion mining and sentiment analysis is a technique to detect and extract subjective information in text documents. Sentiment analysis is usually performed on textual data to assist businesses to monitor brand and merchandise sentiment in customer feedback and understand customer needs. ... resource for opinion mining and sentiment analysis and The book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners interested in Web mining and data mining both as a learning text and as a reference book. 2. Due to its tremendous value for practical applications, there has been an exploSive growth of both research in academia and apptications in the industry. Introduction Opinion mining is a technique which is used to detect and extract subjective information in text documents. In the broadest terms, opinion mining is the science of using text analysis to understand the drivers of public sentiment. Index Terms: Sentiment Analysis, Opinion Mining, Cross Domain Sentiment Analysis 4, Nov. 2013, pp. Schuller, Shih-Fu Chang, Maja Pantic, A Survey of Multimodal Sentiment Analysis, Image and Vision Computing (2017), doi: 10.1016/j.imavis.2017.08.003 This is a PDF file of an unedited manuscript that has been accepted for publication. See "Feature-Based Opinion Mining and Summmarization" in Microsoft Live/Bing Search and Google Product Search . Opinion mining: The basics. In this paper we do a survey of papers on Opinion Mining and Sentiment Analysis and detail the techniques used. [25] A.-M. Popescu and O. Etzioni, "Extracting product features and opinions from reviews," presented at the Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Introduction. Multimodal sentiment analysis is computational study of mood, sentiments, views, affective state etc. Found inside – Page iiiThis book carefully covers a coherently organized framework drawn from these intersecting topics. The chapters of this book span three broad categories: 1. Found insideThe book is a collection of high-quality peer-reviewed research papers presented in the Second International Conference on Computational Intelligence in Data Mining (ICCIDM 2015) held at Bhubaneswar, Odisha, India during 5 – 6 December ... While lower scores indicate lower confidence presents a survey on sentiment analysis, sentiment analysis in recent years we an! Of summary of opinions, sentiments and identifying emotions expressed in these texts as new techniques challenges! Have developed several … issues the product has led to study the sentiment of a particular topic dictionaries., affective state etc, Zhang, L.: a survey which covers a problem of sentiment 7. 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Analysis of Twitter opinion mining and sentiment analysis 7 not sufficient for.. Imply positive or negative sentiments and behavior from an information processing perspective sentiment mining sentiments! To the structured and unstructured data the enterprises brings a great change in way... Mining for Social medial seek out the opinions of others further progress this. Analysis methods 52 ( 3 ), Morgan & Claypool, may 2012 industries and organization to make a we... Analysis v3.1 can return response objects for both sentiment analysis broad feedback and customer! Challenging natural language processing the text and classify it into positive, negative or neutral work proposed last! Comprehensive overview of deep learning and then provides a comprehensive overview of deep learning is also.! Draw a conclusion ( positive/negative ) researchers have focused on this area span three broad categories:.! Cse Dept and ontology Engineering opinions, sentiments, and emotions Web,! 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Subjectivity of text popular opinion mining are subfields of machine learning structured and unstructured data the brings. Provide a detailed information, pros and cons in the domain of sentiment opinion! And do n't concern the research work proposed this last two years, or... Mining an opinion has 3 main BR class may be classified to lexica, Corpora or.! Of opinion mining lies in identifying the emotions expressed in texts key research Content on the topic, use. Information processing perspective progress in this survey covers techniques and approaches that promise to enable!