Visual Question Answering: A Survey of Methods and Datasets

Visual Question Answering (VQA) is a challenging task that has received increasing attention from both the computer vision and the natural language processing communities. Given an image and a question in natural language, it requires reasoning over visual elements of the image and general knowledge to infer the correct answer. In the first part of this survey, we examine the state of the art by comparing modern approaches to the problem. We classify methods by their mechanism to connect the visual and textual modalities. In particular, we examine the common approach of combining convolutional and recurrent neural networks to map images and questions to a common feature space. We also discuss memory-augmented and modular architectures that interface with structured knowledge bases. In the second part of this survey, we review the datasets available for training and evaluating VQA systems. The various datatsets contain questions at different levels of complexity, which require different capabilities and types of reasoning. We examine in depth the question/answer pairs from the Visual Genome project, and evaluate the relevance of the structured annotations of images with scene graphs for VQA. Finally, we discuss promising future directions for the field, in particular the connection to structured knowledge bases and the use of natural language processing models.Comment: 25 page

Absurd Function Upends Familiar Form: Satire, Literary Space-Time, and the Subversion of Deterministic Meta-Narrative in Kurt Vonnegut's The Sirens of Time

In The Sirens of Titan (1959), Vonnegut’s classic satirical humor peppers a narrative that bounces among the planets Mars, Mercury, and Earth, with the characters finally arriving on Saturn’s moon, Titan. In the novel, Kurt Vonnegut crafts a story that symbolically links American culture’s view of itself with evolving perceptions of space, time, and art. Through the careful use of satire and the depiction of various kinds of time, Vonnegut creates a deliberately self-nullifying (yet palatable) narrative whose only offer of hope in the face of a meaningless world is its multifaceted individualized rejection of humankind’s view of its own lofty destiny. Applying the lenses of the aforementioned contextual situations, this paper analyzes and attempts to describe the rhetorical matrix that Vonnegut uses to convey the thesis he layers deeply within the novel. Through the analysis of Vonnegut’s satire and alternative representations of literary time in Sirens, one can conclude that he is critiquing a specific theory of human narrative that relates to fiction as well as lived reality

Automatic Concept Extraction in Semantic Summarization Process

The Semantic Web offers a generic infrastructure for interchange, integration and creative reuse of structured data, which can help to cross some of the boundaries that Web 2.0 is facing. Currently, Web 2.0 offers poor query possibilities apart from searching by keywords or tags. There has been a great deal of interest in the development of semantic-based systems to facilitate knowledge representation and extraction and content integration [1], [2]. Semantic-based approach to retrieving relevant material can be useful to address issues like trying to determine the type or the quality of the information suggested from a personalized environment. In this context, standard keyword search has a very limited effectiveness. For example, it cannot filter for the type of information, the level of information or the quality of information. Potentially, one of the biggest application areas of content-based exploration might be personalized searching framework (e.g., [3],[4]). Whereas search engines provide nowadays largely anonymous information, new framework might highlight or recommend web pages related to key concepts. We can consider semantic information representation as an important step towards a wide efficient manipulation and retrieval of information [5], [6], [7]. In the digital library community a flat list of attribute/value pairs is often assumed to be available. In the Semantic Web community, annotations are often assumed to be an instance of an ontology. Through the ontologies the system will express key entities and relationships describing resources in a formal machine-processable representation. An ontology-based knowledge representation could be used for content analysis and object recognition, for reasoning processes and for enabling user-friendly and intelligent multimedia content search and retrieval. Text summarization has been an interesting and active research area since the 60’s. The definition and assumption are that a small portion or several keywords of the original long document can represent the whole informatively and/or indicatively. Reading or processing this shorter version of the document would save time and other resources [8]. This property is especially true and urgently needed at present due to the vast availability of information. Concept-based approach to represent dynamic and unstructured information can be useful to address issues like trying to determine the key concepts and to summarize the information exchanged within a personalized environment. In this context, a concept is represented with a Wikipedia article. With millions of articles and thousands of contributors, this online repository of knowledge is the largest and fastest growing encyclopedia in existence. The problem described above can then be divided into three steps: • Mapping of a series of terms with the most appropriate Wikipedia article (disambiguation). • Assigning a score for each item identified on the basis of its importance in the given context. • Extraction of n items with the highest score. Text summarization can be applied to many fields: from information retrieval to text mining processes and text display. Also in personalized searching framework text summarization could be very useful. The chapter is organized as follows: the next Section introduces personalized searching framework as one of the possible application areas of automatic concept extraction systems. Section three describes the summarization process, providing details on system architecture, used methodology and tools. Section four provides an overview about document summarization approaches that have been recently developed. Section five summarizes a number of real-world applications which might benefit from WSD. Section six introduces Wikipedia and WordNet as used in our project. Section seven describes the logical structure of the project, describing software components and databases. Finally, Section eight provides some consideration..

Authenticity and originarity in foreign language learning in the diaspora

This paper reflects on a telecollaborative project with second-year students of German between the University of Pretoria (South Africa) and Colgate University (United States of America) in 2008. The project resulted from a critical discussion on the potential of online technology in foreign languagelearning (FLL). A central concern in implementing such technology should be the all-inclusive, authentic use of all language faculties, which Peeters (2008) calls "originarity". The latter overcomes structuralist or poststructuralist reductions of language as a medium of communication. Thus, the essence of FLL can be redefined, not as the acquisition of mimicry of specific codes, but as intercultural dialogue.Keywords: originarity, authenticity, foreign language learning, video conferencin

Web knowledge bases

Knowledge is key to natural language understanding. References to specific people, places and things in text are crucial to resolving ambiguity and extracting meaning. Knowledge Bases (KBs) codify this information for automated systems — enabling applications such as entity-based search and question answering. This thesis explores the idea that sites on the web may act as a KB, even if that is not their primary intent. Dedicated kbs like Wikipedia are a rich source of entity information, but are built and maintained at an ongoing cost in human effort. As a result, they are generally limited in terms of the breadth and depth of knowledge they index about entities. Web knowledge bases offer a distributed solution to the problem of aggregating entity knowledge. Social networks aggregate content about people, news sites describe events with tags for organizations and locations, and a diverse assortment of web directories aggregate statistics and summaries for long-tail entities notable within niche movie, musical and sporting domains. We aim to develop the potential of these resources for both web-centric entity Information Extraction (IE) and structured KB population. We first investigate the problem of Named Entity Linking (NEL), where systems must resolve ambiguous mentions of entities in text to their corresponding node in a structured KB. We demonstrate that entity disambiguation models derived from inbound web links to Wikipedia are able to complement and in some cases completely replace the role of resources typically derived from the KB. Building on this work, we observe that any page on the web which reliably disambiguates inbound web links may act as an aggregation point for entity knowledge. To uncover these resources, we formalize the task of Web Knowledge Base Discovery (KBD) and develop a system to automatically infer the existence of KB-like endpoints on the web. While extending our framework to multiple KBs increases the breadth of available entity knowledge, we must still consolidate references to the same entity across different web KBs. We investigate this task of Cross-KB Coreference Resolution (KB-Coref) and develop models for efficiently clustering coreferent endpoints across web-scale document collections. Finally, assessing the gap between unstructured web knowledge resources and those of a typical KB, we develop a neural machine translation approach which transforms entity knowledge between unstructured textual mentions and traditional KB structures. The web has great potential as a source of entity knowledge. In this thesis we aim to first discover, distill and finally transform this knowledge into forms which will ultimately be useful in downstream language understanding tasks

Computer-Assisted Legal Research

Introduction Reasons to Use CALR Types of CALR Online Services: Lexis-Nexis and Westlaw CD ROM Products Bulletin Board Systems Internethttps://digitalcommons.law.uw.edu/librarians-chapters/1015/thumbnail.jp

An analysis of The Oxford Guide to practical lexicography (Atkins and Rundell 2008)

Since at least a decade ago, the lexicographic community at large has been demanding that a modern textbook be designed - one that Would place corpora in the centre of the lexicographic enterprise. Written by two of the most respected practising lexicographers, this book has finally arrived, and delivers on very many levels. This review article presents a critical analysis of its features

Beyond the Single Story: How Analog Hypertext Facilitates Representation of Multiple Critical Perspectives in an Art Museum Object Study Gallery

This project utilized a form of arts based educational research described as analog hypertext to develop interpretative material representing multiple critical, theoretical, and disciplinary perspectives on objects in a university art museum’s object study gallery. Drawing on scholars’ recommendations for postcolonial interpretation of non-Western art, the project created a web of information, which simultaneously revealed and critiqued the underlying ideologies and power structures shaping the museum’s display in an effort to change existing interpretive practice. The project developed five color-coded thematic self-guided tours—art as commodity, spiritual practice, technology and cultural evolutionism, mortuary rituals, and postcolonial perspectives—presented to the public as an interpretive exhibition invited visitors’ contributions. This paper explores how the analog hypertext functions as both a research tool and a content delivery device for the representation of multiple critical perspectives, fostering interdisciplinary perspectives and visitor meaning-making in the process