Download or read book Visual Information Retrieval using Java and LIRE written by Mathias Lux and published by Morgan & Claypool Publishers. This book was released on 2013-01-01 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt: Visual information retrieval (VIR) is an active and vibrant research area, which attempts at providing means for organizing, indexing, annotating, and retrieving visual information (images and videos) from large, unstructured repositories. The goal of VIR is to retrieve matches ranked by their relevance to a given query, which is often expressed as an example image and/or a series of keywords. During its early years (1995-2000), the research efforts were dominated by content-based approaches contributed primarily by the image and video processing community. During the past decade, it was widely recognized that the challenges imposed by the lack of coincidence between an image's visual contents and its semantic interpretation, also known as semantic gap, required a clever use of textual metadata (in addition to information extracted from the image's pixel contents) to make image and video retrieval solutions efficient and effective. The need to bridge (or at least narrow) the semantic gap has been one of the driving forces behind current VIR research. Additionally, other related research problems and market opportunities have started to emerge, offering a broad range of exciting problems for computer scientists and engineers to work on. In this introductory book, we focus on a subset of VIR problems where the media consists of images, and the indexing and retrieval methods are based on the pixel contents of those images -- an approach known as content-based image retrieval (CBIR). We present an implementation-oriented overview of CBIR concepts, techniques, algorithms, and figures of merit. Most chapters are supported by examples written in Java, using Lucene (an open-source Java-based indexing and search implementation) and LIRE (Lucene Image REtrieval), an open-source Java-based library for CBIR. Table of Contents: Introduction / Information Retrieval: Selected Concepts and Techniques / Visual Features / Indexing Visual Features / LIRE: An Extensible Java CBIR Library / Concluding Remarks
Download or read book Visual Information Retrieval Using Java and LIRE written by Lux Mathias and published by Springer Nature. This book was released on 2022-05-31 with total page 96 pages. Available in PDF, EPUB and Kindle. Book excerpt: Visual information retrieval (VIR) is an active and vibrant research area, which attempts at providing means for organizing, indexing, annotating, and retrieving visual information (images and videos) from large, unstructured repositories. The goal of VIR is to retrieve matches ranked by their relevance to a given query, which is often expressed as an example image and/or a series of keywords. During its early years (1995-2000), the research efforts were dominated by content-based approaches contributed primarily by the image and video processing community. During the past decade, it was widely recognized that the challenges imposed by the lack of coincidence between an image's visual contents and its semantic interpretation, also known as semantic gap, required a clever use of textual metadata (in addition to information extracted from the image's pixel contents) to make image and video retrieval solutions efficient and effective. The need to bridge (or at least narrow) the semantic gap has been one of the driving forces behind current VIR research. Additionally, other related research problems and market opportunities have started to emerge, offering a broad range of exciting problems for computer scientists and engineers to work on. In this introductory book, we focus on a subset of VIR problems where the media consists of images, and the indexing and retrieval methods are based on the pixel contents of those images -- an approach known as content-based image retrieval (CBIR). We present an implementation-oriented overview of CBIR concepts, techniques, algorithms, and figures of merit. Most chapters are supported by examples written in Java, using Lucene (an open-source Java-based indexing and search implementation) and LIRE (Lucene Image REtrieval), an open-source Java-based library for CBIR. Table of Contents: Introduction / Information Retrieval: Selected Concepts and Techniques / Visual Features / Indexing Visual Features / LIRE: An Extensible Java CBIR Library / Concluding Remarks
Download or read book Visual Information Retrieval Using Java and LIRE written by Lux Mathias and published by . This book was released on 2012 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Answer Machine is a practical, non-technical guide to the technologies behind information seeking and analysis. It introduces search and content analytics to software buyers, knowledge managers, and searchers who want to understand and design effective online environments. The book describes how search evolved from an expert-only to an end user tool. It provides an overview of search engines, categorization and clustering, natural language processing, content analytics, and visualization technologies. Detailed profiles for Web search, eCommerce search, eDiscovery, and enterprise search contrast the types of users, uses, tasks, technologies, and interaction designs for each. These variables shape each application, although the underlying technologies are the same. Types of information tasks and the trade-offs between precision and recall, time, volume and precision, and privacy vs. personalization are discussed within this context. The book examines trends toward convenient, context-aware computing, big data and analytics technologies, conversational systems, and answer machines. The Answer Machine explores IBM Watson's DeepQA technology and describes how it is used to answer health care and Jeopardy questions. The book concludes by discussing the implications of these advances: how they will change the way we run our businesses, practice medicine, govern, or conduct our lives in the digital age. Table of Contents: Introduction / The Query Process and Barriers to Finding Information Online / Online Search: An Evolution / Search and Discovery Technologies: An Overview / Information Access: A Spectrum of Needs and Uses / Future Tense: The Next Era in Information Access and Discovery / Answer Machines.
Download or read book Information Retrieval Models written by Thomas Roelleke and published by Springer Nature. This book was released on 2022-05-31 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information Retrieval (IR) models are a core component of IR research and IR systems. The past decade brought a consolidation of the family of IR models, which by 2000 consisted of relatively isolated views on TF-IDF (Term-Frequency times Inverse-Document-Frequency) as the weighting scheme in the vector-space model (VSM), the probabilistic relevance framework (PRF), the binary independence retrieval (BIR) model, BM25 (Best-Match Version 25, the main instantiation of the PRF/BIR), and language modelling (LM). Also, the early 2000s saw the arrival of divergence from randomness (DFR). Regarding intuition and simplicity, though LM is clear from a probabilistic point of view, several people stated: "It is easy to understand TF-IDF and BM25. For LM, however, we understand the math, but we do not fully understand why it works." This book takes a horizontal approach gathering the foundations of TF-IDF, PRF, BIR, Poisson, BM25, LM, probabilistic inference networks (PIN's), and divergence-based models. The aim is to create a consolidated and balanced view on the main models. A particular focus of this book is on the "relationships between models." This includes an overview over the main frameworks (PRF, logical IR, VSM, generalized VSM) and a pairing of TF-IDF with other models. It becomes evident that TF-IDF and LM measure the same, namely the dependence (overlap) between document and query. The Poisson probability helps to establish probabilistic, non-heuristic roots for TF-IDF, and the Poisson parameter, average term frequency, is a binding link between several retrieval models and model parameters. Table of Contents: List of Figures / Preface / Acknowledgments / Introduction / Foundations of IR Models / Relationships Between IR Models / Summary & Research Outlook / Bibliography / Author's Biography / Index
Download or read book Fuzzy Information Retrieval written by Donald H. Kraft and published by Springer Nature. This book was released on 2022-06-01 with total page 63 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information retrieval used to mean looking through thousands of strings of texts to find words or symbols that matched a user's query. Today, there are many models that help index and search more effectively so retrieval takes a lot less time. Information retrieval (IR) is often seen as a subfield of computer science and shares some modeling, applications, storage applications and techniques, as do other disciplines like artificial intelligence, database management, and parallel computing. This book introduces the topic of IR and how it differs from other computer science disciplines. A discussion of the history of modern IR is briefly presented, and the notation of IR as used in this book is defined. The complex notation of relevance is discussed. Some applications of IR is noted as well since IR has many practical uses today. Using information retrieval with fuzzy logic to search for software terms can help find software components and ultimately help increase the reuse of software. This is just one practical application of IR that is covered in this book. Some of the classical models of IR is presented as a contrast to extending the Boolean model. This includes a brief mention of the source of weights for the various models. In a typical retrieval environment, answers are either yes or no, i.e., on or off. On the other hand, fuzzy logic can bring in a "degree of" match, vs. a crisp, i.e., strict match. This, too, is looked at and explored in much detail, showing how it can be applied to information retrieval. Fuzzy logic is often times considered a soft computing application and this book explores how IR with fuzzy logic and its membership functions as weights can help indexing, querying, and matching. Since fuzzy set theory and logic is explored in IR systems, the explanation of where the fuzz is ensues. The concept of relevance feedback, including pseudorelevance feedback is explored for the various models of IR. For the extended Boolean model, the use of genetic algorithms for relevance feedback is delved into. The concept of query expansion is explored using rough set theory. Various term relationships is modeled and presented, and the model extended for fuzzy retrieval. An example using the UMLS terms is also presented. The model is also extended for term relationships beyond synonyms. Finally, this book looks at clustering, both crisp and fuzzy, to see how that can improve retrieval performance. An example is presented to illustrate the concepts.
Download or read book Predicting Information Retrieval Performance written by Robert M. Losee and published by Springer Nature. This book was released on 2022-05-31 with total page 59 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information Retrieval performance measures are usually retrospective in nature, representing the effectiveness of an experimental process. However, in the sciences, phenomena may be predicted, given parameter values of the system. After developing a measure that can be applied retrospectively or can be predicted, performance of a system using a single term can be predicted given several different types of probabilistic distributions. Information Retrieval performance can be predicted with multiple terms, where statistical dependence between terms exists and is understood. These predictive models may be applied to realistic problems, and then the results may be used to validate the accuracy of the methods used. The application of metadata or index labels can be used to determine whether or not these features should be used in particular cases. Linguistic information, such as part-of-speech tag information, can increase the discrimination value of existing terminology and can be studied predictively. This work provides methods for measuring performance that may be used predictively. Means of predicting these performance measures are provided, both for the simple case of a single term in the query and for multiple terms. Methods of applying these formulae are also suggested.
Download or read book Simulating Information Retrieval Test Collections written by David Hawking and published by Springer Nature. This book was released on 2022-06-01 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: Simulated test collections may find application in situations where real datasets cannot easily be accessed due to confidentiality concerns or practical inconvenience. They can potentially support Information Retrieval (IR) experimentation, tuning, validation, performance prediction, and hardware sizing. Naturally, the accuracy and usefulness of results obtained from a simulation depend upon the fidelity and generality of the models which underpin it. The fidelity of emulation of a real corpus is likely to be limited by the requirement that confidential information in the real corpus should not be able to be extracted from the emulated version. We present a range of methods exploring trade-offs between emulation fidelity and degree of preservation of privacy. We present three different simple types of text generator which work at a micro level: Markov models, neural net models, and substitution ciphers. We also describe macro level methods where we can engineer macro properties of a corpus, giving a range of models for each of the salient properties: document length distribution, word frequency distribution (for independent and non-independent cases), word length and textual representation, and corpus growth. We present results of emulating existing corpora and for scaling up corpora by two orders of magnitude. We show that simulated collections generated with relatively simple methods are suitable for some purposes and can be generated very quickly. Indeed it may sometimes be feasible to embed a simple lightweight corpus generator into an indexer for the purpose of efficiency studies. Naturally, a corpus of artificial text cannot support IR experimentation in the absence of a set of compatible queries. We discuss and experiment with published methods for query generation and query log emulation. We present a proof-of-the-pudding study in which we observe the predictive accuracy of efficiency and effectiveness results obtained on emulated versions of TREC corpora. The study includes three open-source retrieval systems and several TREC datasets. There is a trade-off between confidentiality and prediction accuracy and there are interesting interactions between retrieval systems and datasets. Our tentative conclusion is that there are emulation methods which achieve useful prediction accuracy while providing a level of confidentiality adequate for many applications. Many of the methods described here have been implemented in the open source project SynthaCorpus, accessible at: https://bitbucket.org/davidhawking/synthacorpus/
Download or read book Dynamic Information Retrieval Modeling written by Grace Hui Yang and published by Springer Nature. This book was released on 2022-05-31 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data and human-computer information retrieval (HCIR) are changing IR. They capture the dynamic changes in the data and dynamic interactions of users with IR systems. A dynamic system is one which changes or adapts over time or a sequence of events. Many modern IR systems and data exhibit these characteristics which are largely ignored by conventional techniques. What is missing is an ability for the model to change over time and be responsive to stimulus. Documents, relevance, users and tasks all exhibit dynamic behavior that is captured in data sets typically collected over long time spans and models need to respond to these changes. Additionally, the size of modern datasets enforces limits on the amount of learning a system can achieve. Further to this, advances in IR interface, personalization and ad display demand models that can react to users in real time and in an intelligent, contextual way. In this book we provide a comprehensive and up-to-date introduction to Dynamic Information Retrieval Modeling, the statistical modeling of IR systems that can adapt to change. We define dynamics, what it means within the context of IR and highlight examples of problems where dynamics play an important role. We cover techniques ranging from classic relevance feedback to the latest applications of partially observable Markov decision processes (POMDPs) and a handful of useful algorithms and tools for solving IR problems incorporating dynamics. The theoretical component is based around the Markov Decision Process (MDP), a mathematical framework taken from the field of Artificial Intelligence (AI) that enables us to construct models that change according to sequential inputs. We define the framework and the algorithms commonly used to optimize over it and generalize it to the case where the inputs aren't reliable. We explore the topic of reinforcement learning more broadly and introduce another tool known as a Multi-Armed Bandit which is useful for cases where exploring model parameters is beneficial. Following this we introduce theories and algorithms which can be used to incorporate dynamics into an IR model before presenting an array of state-of-the-art research that already does, such as in the areas of session search and online advertising. Change is at the heart of modern Information Retrieval systems and this book will help equip the reader with the tools and knowledge needed to understand Dynamic Information Retrieval Modeling.
Download or read book Mining Multimedia Documents written by Wahiba Ben Abdessalem Karaa and published by CRC Press. This book was released on 2017-04-21 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: The information age has led to an explosion in the amount of information available to the individual and the means by which it is accessed, stored, viewed, and transferred. In particular, the growth of the internet has led to the creation of huge repositories of multimedia documents in a diverse range of scientific and professional fields, as well as the tools to extract useful knowledge from them. Mining Multimedia Documents is a must-read for researchers, practitioners, and students working at the intersection of data mining and multimedia applications. It investigates various techniques related to mining multimedia documents based on text, image, and video features. It provides an insight into the open research problems benefitting advanced undergraduates, graduate students, researchers, scientists and practitioners in the fields of medicine, biology, production, education, government, national security and economics.
Download or read book Information Security and Cryptology ICISC 2014 written by Jooyoung Lee and published by Springer. This book was released on 2015-03-16 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of the 17th International Conference on Information Security and Cryptology, ICISC 2014, held in Seoul, South Korea in December 2014. The 27 revised full papers presented were carefully selected from 91 submissions during two rounds of reviewing. The papers provide the latest results in research, development and applications in the field of information security and cryptology. They are organized in topical sections on RSA security, digital signature, public key cryptography, block ciphers, network security, mobile security, hash functions, information hiding and efficiency, cryptographic protocol, and side-channel attacks.
Download or read book Multimodal Behavior Analysis in the Wild written by Xavier Alameda-Pineda and published by Academic Press. This book was released on 2018-11-13 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multimodal Behavioral Analysis in the Wild: Advances and Challenges presents the state-of- the-art in behavioral signal processing using different data modalities, with a special focus on identifying the strengths and limitations of current technologies. The book focuses on audio and video modalities, while also emphasizing emerging modalities, such as accelerometer or proximity data. It covers tasks at different levels of complexity, from low level (speaker detection, sensorimotor links, source separation), through middle level (conversational group detection, addresser and addressee identification), and high level (personality and emotion recognition), providing insights on how to exploit inter-level and intra-level links. This is a valuable resource on the state-of-the- art and future research challenges of multi-modal behavioral analysis in the wild. It is suitable for researchers and graduate students in the fields of computer vision, audio processing, pattern recognition, machine learning and social signal processing. Gives a comprehensive collection of information on the state-of-the-art, limitations, and challenges associated with extracting behavioral cues from real-world scenarios Presents numerous applications on how different behavioral cues have been successfully extracted from different data sources Provides a wide variety of methodologies used to extract behavioral cues from multi-modal data
Download or read book Exploring Context in Information Behavior written by Naresh Kumar Agarwal and published by Springer Nature. This book was released on 2022-05-31 with total page 163 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of human information behavior runs the gamut of processes from the realization of a need or gap in understanding, to the search for information from one or more sources to fill that gap, to the use of that information to complete a task at hand or to satisfy a curiosity, as well as other behaviors such as avoiding information or finding information serendipitously. Designers of mechanisms, tools, and computer-based systems to facilitate this seeking and search process often lack a full knowledge of the context surrounding the search. This context may vary depending on the job or role of the person; individual characteristics such as personality, domain knowledge, age, gender, perception of self, etc.; the task at hand; the source and the channel and their degree of accessibility and usability; and the relationship that the seeker shares with the source. Yet researchers have yet to agree on what context really means. While there have been various research studies incorporating context, and biennial conferences on context in information behavior, there lacks a clear definition of what context is, what its boundaries are, and what elements and variables comprise context. In this book, we look at the many definitions of and the theoretical and empirical studies on context, and I attempt to map the conceptual space of context in information behavior. I propose theoretical frameworks to map the boundaries, elements, and variables of context. I then discuss how to incorporate these frameworks and variables in the design of research studies on context. We then arrive at a unified definition of context. This book should provide designers of search systems a better understanding of context as they seek to meet the needs and demands of information seekers. It will be an important resource for researchers in Library and Information Science, especially doctoral students looking for one resource that covers an exhaustive range of the most current literature related to context, the best selection of classics, and a synthesis of these into theoretical frameworks and a unified definition. The book should help to move forward research in the field by clarifying the elements, variables, and views that are pertinent. In particular, the list of elements to be considered, and the variables associated with each element will be extremely useful to researchers wanting to include the influences of context in their studies.
Download or read book Researching Serendipity in Digital Information Environments written by Lori McCay-Peet and published by Springer Nature. This book was released on 2022-05-31 with total page 91 pages. Available in PDF, EPUB and Kindle. Book excerpt: Chance, luck, and good fortune are the usual go-to descriptors of serendipity, a phenomenon aptly often coupled with famous anecdotes of accidental discoveries in engineering and science in modern history such as penicillin, Teflon, and Post-it notes. Serendipity, however, is evident in many fields of research, in organizations, in everyday life—and there is more to it than luck implies. While the phenomenon is strongly associated with in person interactions with people, places, and things, most attention of late has focused on its preservation and facilitation within digital information environments. Serendipity's association with unexpected, positive user experiences and outcomes has spurred an interest in understanding both how current digital information environments support serendipity and how novel approaches may be developed to facilitate it. Research has sought to understand serendipity, how it is manifested in people's personality traits and behaviors, how it may be facilitated in digital information environments such as mobile applications, and its impacts on an individual, an organizational, and a wider level. Because serendipity is expressed and understood in different ways in different contexts, multiple methods have been used to study the phenomenon and evaluate digital information environments that may support it. This volume brings together different disciplinary perspectives and examines the motivations for studying serendipity, the various ways in which serendipity has been approached in the research, methodological approaches to build theory, and how it may be facilitated. Finally, a roadmap for serendipity research is drawn by integrating key points from this volume to produce a framework for the examination of serendipity in digital information environments.
Download or read book The Notion of Relevance in Information Science written by Tefko Saracevic and published by Springer Nature. This book was released on 2022-05-31 with total page 109 pages. Available in PDF, EPUB and Kindle. Book excerpt: Everybody knows what relevance is. It is a "ya'know" notion, concept, idea–no need to explain whatsoever. Searching for relevant information using information technology (IT) became a ubiquitous activity in contemporary information society. Relevant information means information that pertains to the matter or problem at hand—it is directly connected with effective communication. The purpose of this book is to trace the evolution and with it the history of thinking and research on relevance in information science and related fields from the human point of view. The objective is to synthesize what we have learned about relevance in several decades of investigation about the notion in information science. This book deals with how people deal with relevance—it does not cover how systems deal with relevance; it does not deal with algorithms. Spurred by advances in information retrieval (IR) and information systems of various kinds in handling of relevance, a number of basic questions are raised: But what is relevance to start with? What are some of its properties and manifestations? How do people treat relevance? What affects relevance assessments? What are the effects of inconsistent human relevance judgments on tests of relative performance of different IR algorithms or approaches? These general questions are discussed in detail.
Download or read book Transforming Technologies to Manage Our Information written by William Jones and published by Springer Nature. This book was released on 2022-05-31 with total page 155 pages. Available in PDF, EPUB and Kindle. Book excerpt: With its theme, "Our Information, Always and Forever," Part I of this book covers the basics of personal information management (PIM) including six essential activities of PIM and six (different) ways in which information can be personal to us. Part I then goes on to explore key issues that arise in the "great migration" of our information onto the Web and into a myriad of mobile devices. Part 2 provides a more focused look at technologies for managing information that promise to profoundly alter our practices of PIM and, through these practices, the way we lead our lives. Part 2 is in five chapters: - Chapter 5. Technologies of Input and Output. Technologies in support of gesture, touch, voice, and even eye movements combine to support a more natural user interface (NUI). Technologies of output include glasses and "watch" watches. Output will also increasingly be animated with options to "zoom". - Chapter 6. Technologies to Save Our Information. We can opt for "life logs" to record our experiences with increasing fidelity. What will we use these logs for? And what isn’t recorded that should be? - Chapter 7. Technologies to Search Our Information. The potential for personalized search is enormous and mostly yet to be realized. Persistent searches, situated in our information landscape, will allow us to maintain a diversity of projects and areas of interest without a need to continually switch from one to another to handle incoming information. - Chapter 8. Technologies to Structure Our Information. Structure is key if we are to keep, find, and make effective use of our information. But how best to structure? And how best to share structured information between the applications we use, with other people, and also with ourselves over time? What lessons can we draw from the failures and successes in web-based efforts to share structure? - Chapter 9. PIM Transformed and Transforming: Stories from the Past, Present and Future. Part 2 concludes with a comparison between Licklider’s world of information in 1957 and our own world of information today. And then we consider what the world of information is likely to look like in 2057. Licklider estimated that he spent 85% of his "thinking time" in activities that were clerical and mechanical and might (someday) be delegated to the computer. What percentage of our own time is spent with the clerical and mechanical? What about in 2057?
Download or read book Artificial Intelligence Research and Development written by A. Nebot and published by IOS Press. This book was released on 2016-09-21 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Catalan Association for Artificial Intelligence (ACIA) was formed in 1994 with the aim of promoting cooperation between researchers in artificial intelligence within the Catalan speaking community. This objective has been achieved and widened since the association held their first conference in 1998, and the annual conference of the association has become an international event presenting and discussing the latest research in AI, which attracts AI researchers from around the world. This book presents the proceedings of the 19th International Conference of the Catalan Association for Artificial Intelligence (CCIA 2016), held in Barcelona, Spain, on 19-21 October. From a total of 50 original contributions, 16 long papers and 22 short papers were accepted for presentation at the conference on the basis of their relevance, originality and technical validity. The book is divided into 7 sections: Invited Talks (synopsis only); Vision and Robotics; Logic, Constraint Satisfaction and Qualitative Theory; Classification and Clustering; Modelling; Planning and Recommender Systems; Lexical Knowledge Representation and Natural Language Processing. Providing an overview of the latest developments in the field, this book will be of interest to all those whose work involves research into, and the application of, artificial intelligence.
Download or read book Framing Privacy in Digital Collections with Ethical Decision Making written by Virginia Dressler and published by Springer Nature. This book was released on 2022-06-01 with total page 85 pages. Available in PDF, EPUB and Kindle. Book excerpt: As digital collections continue to grow, the underlying technologies to serve up content also continue to expand and develop. As such, new challenges are presented which continue to test ethical ideologies in everyday environs of the practitioner. There are currently no solid guidelines or overarching codes of ethics to address such issues. The digitization of modern archival collections, in particular, presents interesting conundrums when factors of privacy are weighed and reviewed in both small and mass digitization initiatives. Ethical decision making needs to be present at the onset of project planning in digital projects of all sizes, and we also need to identify the role and responsibility of the practitioner to make more virtuous decisions on behalf of those with no voice or awareness of potential privacy breaches. In this book, notions of what constitutes private information are discussed, as is the potential presence of such information in both analog and digital collections. This book lays groundwork to introduce the topic of privacy within digital collections by providing some examples from documented real-world scenarios and making recommendations for future research. A discussion of the notion privacy as concept will be included, as well as some historical perspective (with perhaps one the most cited work on this topic, for example, Warren and Brandeis' "Right to Privacy," 1890). Concepts from the The Right to Be Forgotten case in 2014 (Google Spain SL, Google Inc. v Agencia Españla de Protección de Datos, Mario Costeja González) are discussed as to how some lessons may be drawn from the response in Europe and also how European data privacy laws have been applied. The European ideologies are contrasted with the Right to Free Speech in the First Amendment in the U.S., highlighting the complexities in setting guidelines and practices revolving around privacy issues when applied to real life scenarios. Two ethical theories are explored: Consequentialism and Deontological. Finally, ethical decision making models will also be applied to our framework of digital collections. Three case studies are presented to illustrate how privacy can be defined within digital collections in some real-world examples.