Notes:
Machine reading is the ability of a machine or computer program to automatically extract and understand the meaning of text. It is a subfield of natural language processing (NLP) that focuses on enabling machines to understand the content and structure of written text, and to use that understanding to perform various tasks.
Machine reading involves several different processes, including text segmentation, parsing, and summarization. In order to read text, a machine must first be able to segment the text into individual words, phrases, and sentences. It must then be able to parse the text, that is, to analyze its structure and identify the relationships between words and phrases. Finally, it must be able to summarize the text, extracting the most important and relevant information and using it to answer questions or perform other tasks.
Machine reading is a challenging problem, because it requires a machine to have a deep understanding of language, including grammar, semantics, and context. However, advances in natural language processing and machine learning have made it possible for machines to read text with increasing accuracy and speed.
Machine reading is a valuable tool for many applications, including information retrieval, question answering, and automatic summarization. It is also an important component of many artificial intelligence (AI) systems, including dialog systems, virtual assistants, and intelligent tutoring systems.
References:
See also:
Machine Reading. O Etzioni, M Banko, MJ Cafarella – AAAI, 2006 – aaai.org The time is ripe for the AI community to set its sights on Machine Reading—the autonomous understanding of text. Below, we place the notion of “Machine Reading” in context, describe progress towards this goal by the KnowItAll research group at the University of … Cited by 86 Related articles All 20 versions
Robust Graph Alignment Methods for Textual Inference and Machine Reading. MC de Marneffe, T Grenager, B MacCartney… – … : Machine Reading, 2007 – aaai.org Abstract This paper presents our work on textual inference and situates it within the context of the larger goals of machine reading. The textual inference task is to determine if the meaning of one text can be inferred from the meaning of another combined with … Cited by 24 Related articles All 19 versions
LCC’s GISTexter at DUC 2007: Machine reading for update summarization A Hickl, K Roberts, F Lacatusu – Proc. of DUC, 2007 – duc.nist.gov Abstract In this paper, we describe Language Computer Corporation’s GISTEXTER question- focused and update-based multidocument summarization (MDS) systems. We show that by using a machine reading (MR) framework in order to construct representations of the … Cited by 17 Related articles All 4 versions
Machine reading at the university of washington H Poon, J Christensen, P Domingos, O Etzioni… – Proceedings of the …, 2010 – dl.acm.org Abstract Machine reading is a long-standing goal of AI and NLP. In recent years, tremendous progress has been made in developing machine learning approaches for many of its subtasks such as parsing, information extraction, and question answering. However, … Cited by 16 Related articles All 17 versions
Reporting on Some Logic-Based Machine Reading Research. S Bringsjord, K Arkoudas, M Clark, A Shilliday… – … : Machine Reading, 2007 – aaai.org Much sponsored research in our lab either falls under or intersects with machine reading. In this short paper we give an encapsulated presentation of some of the research in question, leaving aside, for the most part, the considerable detailed technical information that … Cited by 15 Related articles All 7 versions
The DARPA Machine Reading Program-Encouraging Linguistic and Reasoning Research with a Series of Reading Tasks. S Strassel, D Adams, H Goldberg, J Herr, R Keesing… – LREC, 2010 – duck.franz.com Abstract The goal of DARPA’s Machine Reading (MR) program is nothing less than making the world’s natural language corpora available for formal processing. Most text processing research has focused on locating mission-relevant text (information retrieval) and on … Cited by 14 Related articles All 16 versions
Filling knowledge gaps in text for machine reading A Peñas, E Hovy – Proceedings of the 23rd International Conference on …, 2010 – dl.acm.org Abstract Texts are replete with gaps, information omitted since authors assume a certain amount of background knowledge. We define the process of enrichment that fills these gaps. We describe how enrichment can be performed using a Background Knowledge Base … Cited by 15 Related articles All 6 versions
Answering and Questioning for Machine Reading. L Vanderwende – AAAI Spring Symposium: Machine Reading, 2007 – aaai.org Abstract Machine reading can be defined as the automatic understanding of text. One way in which human understanding of text has been gauged is to measure the ability to answer questions pertaining to the text. In this paper, we present a brief study designed to explore … Cited by 8 Related articles All 11 versions
Post-Human Mimesis and the Debunked Machine: Reading Environmental Appropriation in Poe’s “Maelzel’s Chess-Player” and “The Man That Was Used Up” J Berkley – Comparative Literature Studies, 2004 – muse.jhu.edu The cultural and academic debates about the status of the human subject in an increasingly technological world may seem to have cooled slightly since the fin-de-siècle ferment of the 1990s, a time when 1980s hypotheses about cyberspace, cyborgs, and non-human … Cited by 8 Related articles All 4 versions
Machine reading using markov logic networks for collective probabilistic inference S Ghosh, N Shankar, S Owre – In Proceedings of ECML-CoLISD, 2011 – csl.sri.com Abstract. DARPA’s Machine Reading project is directed at extracting specific information from natural language text such as events from news articles. We describe a component of FAUST, a system designed for machine reading, which combines stateof-the-art … Cited by 10 Related articles All 3 versions
Extreme extraction: machine reading in a week M Freedman, L Ramshaw, E Boschee… – Proceedings of the …, 2011 – dl.acm.org Abstract We report on empirical results in extreme extraction. It is extreme in that (1) from receipt of the ontology specifying the target concepts and relations, development is limited to one week and that (2) relatively little training data is assumed. We are able to surpass … Cited by 11 Related articles All 4 versions
Machine reading of web text O Etzioni – Proceedings of the 4th international conference on …, 2007 – dl.acm.org Over the last five years or so, the KnowItAll project at the University of Washington has been investigating the hypothesis that a substantial fraction of the knowledge necessary for intelligence can be extracted automatically from text, and specifically from text available … Cited by 6 Related articles All 2 versions
Machine Reading: A “Killer App” for Statistical Relational AI. H Poon, P Domingos – Statistical Relational Artificial Intelligence, 2010 – aaai.org Abstract Machine reading aims to automatically extract knowledge from text. It is a long- standing goal of AI and holds the promise of revolutionizing Web search and other fields. In this paper, we analyze the core challenges of machine reading and show that statistical … Cited by 6 Related articles All 12 versions
Machine reading of camera-held low quality text images: an ICA-based image enhancement approach for improving OCR accuracy U Garain, A Jain, A Maity… – Pattern Recognition, 2008. …, 2008 – ieeexplore.ieee.org Abstract An Independent Component Analysis (ICA)-based image enhancement technique is presented to improve the accuracy for machine reading of camera-based images. Images of inscriptions that are normally engraved on stones or other durable materials and found … Cited by 5 Related articles All 4 versions
Annotating modality and negation for a machine reading evaluation R Morante, W Daelemans – 2011 – eprints.pascal-network.org Abstract In this paper we describe the task Processing modality and negation for machine reading, which was organized as a pilot task of the Question Answering for Machine Reading Evaluation (QA4MRE) Lab at CLEF 2011. We dene the aspects of meaning on … Cited by 7 Related articles All 12 versions
Machine Reading of Biomedical Texts about Alzheimer’s Disease 1 R Morante, M Krallinger, A Valencia, W Daelemans – 2012 – Citeseer Abstract. This report describes the task Machine reading of biomedical texts about Alzheimer’s disease, which is a pilot task of the Question Answering for Machine Reading Evaluation (QA4MRE) Lab at CLEF 2012. The task aims at exploring the ability of a … Cited by 7 Related articles
Confabulation based sentence completion for machine reading Q Qiu, Q Wu, DJ Burns, MJ Moore… – … , Mind, and Brain ( …, 2011 – ieeexplore.ieee.org Abstract—Sentence completion and prediction refers to the capability of filling missing words in any incomplete sentences. It is one of the keys to reading comprehension, thus making sentence completion an indispensible component of machine reading. Cogent … Cited by 6 Related articles All 3 versions
Arabic QA4MRE at CLEF 2012: Arabic Question Answering for Machine Reading Evaluation. O Trigui, LH Belguith, P Rosso, HB Amor… – … Online Working Notes …, 2012 – users.dsic.upv.es Abstract. This paper presents the work carried out at ANLP Research Group for the CLEF- QA4MRE 2012 competition. This year, the Arabic language was introduced for the first time on QA4MRE lab at CLEF whose intention was to ask questions which require a deep … Cited by 4 Related articles All 4 versions
Question Answering for Machine Reading with Lexical Chain. L Cao, X Qiu, X Huang – CLEF (Notebook Papers/Labs/ …, 2011 – ims-sites.dei.unipd.it Abstract. Question answering for machine reading (QA4MR) is a task to understand the meaning communicated by a text. In this paper, we present our system in QA4MRE 1. The system follows the steps of reading comprehension as a language learner. Lexical chain … Cited by 4 Related articles All 3 versions
Using Episodic Memory in a Memory Based Parser to Assist Machine Reading. K Livingston, C Riesbeck – AAAI Spring Symposium: Machine Reading, 2007 – aaai.org Abstract The central task for a Machine Reader is integrating information acquired from text with the machine’s existing knowledge. Direct Memory Access Parsing (DMAP) is a machine reading approach that leverages existing knowledge and performs integration in the early … Cited by 4 Related articles All 7 versions
Question Answering for Machine Reading Evaluation. Á Rodrigo, A Peñas, EH Hovy… – … Notebook Papers/LABs/ …, 2010 – clef2010.clef-initiative.eu Abstract. Question Answering (QA) evaluation potentially provides a way to evaluate systems that attempt to understand texts automatically. Although current QA technologies are still unable to answer complex questions that require deep inference, we believe QA … Cited by 3 Related articles All 6 versions
Retrieval-based Question Answering for Machine Reading Evaluation. S Verberne – CLEF (Notebook Papers/Labs/Workshop), 2011 – sverberne.ruhosting.nl Abstract. The Question Answering for Machine Reading (QA4MRE) task was set up as a reading comprehension test consisting of 120 multiple-choice questions pertaining to twelve target texts (the test documents) grouped in three different topics. Since this is the first year … Cited by 2 Related articles All 5 versions
A Study of Machine Reading from Multiple Texts. P Clark, JA Thompson – AAAI Spring Symposium: Learning by Reading and …, 2009 – aaai.org Abstract A system that seeks to build a semantically coherent representation from multiple texts requires (at least) three things: a representation language that is sufficiently expressive to capture the information conveyed by the text; a natural language engine that can … Cited by 3 Related articles All 6 versions
Index Expansion for Machine Reading and Question Answering. G Attardi, L Atzori, M Simi – CLEF (Online Working Notes/Labs/ …, 2012 – ims-sites.dei.unipd.it Abstract. The paper reports our experiments in tackling the CLEF 2012 Pilot Task on Machine Reading for Question Answering. We introduce the technique of index expansion, which relies on building a search index enriched with information gathered from a … Cited by 3 Related articles
Machine reading as a process of partial question-answering P Clark, P Harrison – Proceedings of the NAACL HLT 2010 First …, 2010 – dl.acm.org Abstract This paper explores the close relationship between question answering and machine reading, and how the active use of reasoning to answer (and in the process, disambiguate) questions can also be applied to reading declarative texts, where a … Cited by 2 Related articles All 7 versions
QA4MRE 2011-2013: Overview of Question Answering for Machine Reading Evaluation A Peñas, E Hovy, P Forner, Á Rodrigo… – Information Access …, 2013 – Springer Abstract This paper describes the methodology for testing the performance of Machine Reading systems through Question Answering and Reading Comprehension Tests. This was the attempt of the QA4MRE challenge which was run as a Lab at CLEF 2011–2013. … Cited by 3 Related articles All 2 versions
Machine reading: from wikipedia to the web F Wu – 2010 – redesign.cs.washington.edu In presenting this dissertation in partial fulfillment of the requirements for the doctoral degree at the University of Washington, I agree that the Library shall make its copies freely available for inspection. I further agree that extensive copying of this dissertation is allowable only … Cited by 2 Related articles All 11 versions
Biomedical Text Mining about Alzheimer’s Diseases for Machine Reading Evaluation. BH Tsai, YZ Liu, WJ Hou – CLEF (Online Working Notes/Labs/ …, 2012 – ims-sites.dei.unipd.it Abstract. The paper presents the experiments carried out as part of the participation in the pilot task of Biomedical about Alzheimer for QA4MRE at CLEF 2012. We have submitted total five unique runs in the pilot task. One run uses Term Frequency (TF) of the query … Cited by 1 Related articles
Machine reading between the lines: A simple evaluation framework for extracted knowledge bases A Sil, A Yates, B St, M Ave – Proceedings of the Workshop on Information …, 2011 – aclweb.org Abstract The traditional method to evaluate a knowledge extraction system is to measure precision and recall. But this method only partially measures the quality of a knowledge base (KB) as it cannot predict whether a KB is useful or not. One of the ways in which a KB … Cited by 2 Related articles All 6 versions
Exploiting Inference to Improve Temporal RDF Annotations and Queries for Machine Reading. R Schrag – STIDS, 2012 – franz.com Abstract—We describe existing and anticipated future benefits of an end-to-end methodology for annotating formal RDF statements representing temporal knowledge to be extracted from text, as well as for authoring and validating test and/or application queries … Cited by 1 Related articles All 15 versions
Machine Reading through Textual and Knowledge Entailment. A Hickl, SM Harabagiu – AAAI Spring Symposium: Machine Reading, 2007 – aaai.org Abstract While information extraction and textual entailment systems have greatly enhanced the amount of knowledge available from a text corpus, the next generation of natural language understanding systems–such as Machine Reading systems–will need to … Cited by 1 Related articles All 3 versions
Machine Reading as a Cognitive Science Research Instrument KD Forbus, K Lockwood, E Tomai, M Dehghani… – … : Machine Reading, 2007 – aaai.org Abstract We describe how we are using natural language techniques to develop systems that can automatically encode a range of input materials for cognitive simulations. We start by summarizing this type of problem, and the components we are using. We then describe … Cited by 1 Related articles All 11 versions
Story-Level Inference and Gap Filling to Improve Machine Reading. H Chalupsky – FLAIRS Conference, 2012 – aaai.org Abstract Machine reading aims at extracting formal knowledge representations from text to enable programs to execute some performance task, for example, diagnosis or answering complex queries stated in a formal representation language. Information extraction … Cited by 2 Related articles All 8 versions
Machine reading tea leaves: Automatically evaluating topic coherence and topic model quality JH Lau, D Newman, T Baldwin – Proceedings of the European Chapter of …, 2014 – aclweb.org Abstract Topic models based on latent Dirichlet allocation and related methods are used in a range of user-focused tasks including document navigation and trend analysis, but evaluation of the intrinsic quality of the topic model and topics remains an open research … Cited by 9 Related articles All 3 versions
SKIMMR: Facilitating knowledge discovery in life sciences by machine-aided skim reading V Novacek, GAPC Burns – 2014 – peerj.com … Keywords: Machine Reading, Skim Reading, Publication Search, Text Mining, Information 45 Visualisation 1 Introduction In recent years, knowledge workers in life sciences are increasingly overwhelmed by an ever- growing quantity of information. … Cited by 2 Related articles All 2 versions
Machine Poetics and Reading Machines: William Poundstone’s Electronic Literature and Bob Brown’s Readies J Pressman – American Literary History, 2011 – Oxford Univ Press … minds of others” (168). Carrying words “faster and farther into the minds of others” is the ambition of the particular type of machine reading that inspires Poundstone’s “Project”—subliminal messaging. Although Brown is technically … Cited by 2 Related articles All 4 versions
Evaluating Machine Reading Systems through Comprehension Tests. A Peñas, EH Hovy, P Forner, Á Rodrigo, RFE Sutcliffe… – LREC, 2012 – lrec.elra.info Abstract This paper describes a methodology for testing and evaluating the performance of Machine Reading systems through Question Answering and Reading Comprehension Tests. The methodology is being used in QA4MRE (QA for Machine Reading Evaluation), … Cited by 2 Related articles All 4 versions
Question Answering For Machine Reading Alzheimer’s Task: Team 4 R Das, C He, C Hou, A Lukic, C Wang – cs.cmu.edu Abstract These are the working notes describing the process of improving an existing questionanswering pipeline for the CLEF 2013 Question Answering for Machine Reading Alzheimer’s Task. By performing error analyses on the baseline system, we were able to … Related articles
Mechanism of Human Reading-drawings and its Application in Machine Reading-drawings YHFY Ruo-Yu, LUTCAI Shi-Jie – Computer Science, 2008 – en.cnki.com.cn Machine reading-drawings is an important technique that aims for improving automatization and information-based of construction industry. After analyzing representation characteristics of architectural drawings from the point of view of machine reading- …
Knowledge integration in machine reading DS Kim – 2011 – repositories.lib.utexas.edu Abstract: Machine reading is the arti?cial-intelligence task of automatically reading a corpus of texts and, from the contents, building a knowledge base that supports automated reasoning and question answering. Success at this task could fundamentally solve the … All 2 versions
Brain Box Machine Reading Brainwaves: Mind Reading Computer M Yadav, G Chhillar, J Abhrahm – International …, 2014 – internationaljournalofresearch.org Abstract In the last few decades, many innovative inventions has been done with the growth in the modern technology and Mind Reading Computer is one of them. Mind Reading Computer, part of a neuroscience, is a machine that can interpret and respond to the …
Machine Reading Tea Leaves: Automatically Evaluating Topic Coherence and Topic Model Quality T Baldwin – 2014 – atp-webproxy1.it.nicta.com.au Page 1. Machine Reading Tea Leaves: Automatically Evaluating Topic Coherence and Topic Model Quality Timothy Baldwin … In summary, correlation is computed for 900 topics (3 topic models × (50+100+150) topics) for each domain Wiki and News. Machine Reading Tea Le Related articles All 5 versions
Bayesian Logic Programs for Plan Recognition and Machine Reading SV Raghavan – 2012 – DTIC Document Abstract: Several real world tasks involve data that is uncertain and relational in nature. Traditional approaches like first-order logic and probabilistic models either deal with structured data or uncertainty, but not both. To address these limitations, statistical … Cited by 1 Related articles All 3 versions
Extending Bayesian Logic Programs for Plan Recognition and Machine Reading SV Raghavan – 2011 – DTIC Document Abstract: Statistical relational learning (SRL) is the area of machine learning that integrates both first-order logic and probabilistic graphical models. The advantage of these formalisms is that they can handle both uncertainty and structured/relational data. As a result, they are … Related articles All 6 versions
Knowledge Integration in Machine Reading KJ Barker, V Lifschitz – repositories.lib.utexas.edu First and foremost, I would like to thank my advisor, Bruce Porter, for guiding me through the long journey of my PhD research. Beyond being an academic advisor, he has been my mentor and role model in everything. It is truly a blessing to have studied with him. I would … Related articles All 2 versions
Behind the Word Clouds: Electronic Text, Machine Reading and Corpus Linguistics: Tim Shortis Argues That Corpus Linguistics Is Changing Knowledge about … T Shortis – 2009 – questia.com Hyperbole comes easily in the excited discourse around the impact of ICTs and their ongoing penultimate promises. So it is with caution that I am suggesting that there is a quiet revolution going on in what counts as knowledge about language and meaningful reading … Related articles
Human Word Recognition Compared with Machine Reading M Schenkel, C Latimer, M Jabri – researchgate.net Abstract We present a study which is concerned with word recognition rates for heavily degraded documents. We compare human with machine reading capabilities in a series of experiments, which explores the interaction of word/non-word recognition, word frequency … Related articles All 3 versions
Recognizing Textual Entailment, QA4MRE, and Machine Reading. P Clark – CLEF (Online Working Notes/Labs/Workshop), 2012 – ims-sites.dei.unipd.it Abstract Machine Reading remains one of the Grand Challenges of Artificial Intelligence, and also one of the most difficult. Machine Reading requires more than just parsing a text; it requires constructing a coherent internal model of the world which that text is describing, …
Machine reading at web scale O Etzioni – Proceedings of the 2008 International Conference on …, 2008 – dl.acm.org What will “Web search” look like in ten, twenty, or even fifty years? Should the exponential progress of Moore’s Law raise our ambitions for search technology? Over the last five years or so, the KnowItAll project at the University of Washington has been investigating the … Related articles
Machine Reading: In The Cage S Stivers – 2011 – lcm.english.ucsb.edu When beginning my research for this project I have to admit I was very skeptical. Although the array of world clouds and link charts appeared aesthetically pleasing I was very suspicious of their actual worth when it came down to close reading analysis of the text. … All 2 versions
Using a Question-Answering Approach In Machine Reading Task Of Biomedical Texts About The Alzheimer D Vishnyakova, J Gobeill, P Ruch – ims-sites.dei.unipd.it Abstract. For the machine-reading task of biomedical texts about the Alzheimer disease we have used a Question-Answering approach by adapting functionalities of Question- Answering (QA) engine EAGLi. We didn’t involve any other Natural Language Processing …
Toward a Reading Machine A Peñas – nlp.uned.es … Page 3. UNED nlp.uned.es The goal of Machine Reading ? To build a machine that transforms texts into representations ? that enable inference and reasoning … Page 4. UNED nlp.uned.es The goal of Machine Reading ? This goal is not new ? It is an old dream … Related articles All 4 versions
A Computational Model For Human And Machine Reading JJ Hull – jonathanjhull.com The reading of text by computer without human intervention remains an elusive goal of Artificial Intelligence research. Reading is the transformation of an arbitrary page of text, that could contain a mixture of machine-printed, hand-printed, or handwritten text, from its … Related articles All 4 versions
Reading (Between) Machine J Pressman – American Book Review, 2014 – muse.jhu.edu … Download PDF. Reading (Between) Machine. … poetry and games. It crosses over and comments upon the connection between machine reading and machine writing, between augmented reality and avant-garde literature. It pulls …
Cosine Similarity as Machine Reading Technique. G Arora, P Majumder – CLEF (Notebook Papers/Labs/ …, 2011 – clef2011.clef-initiative.eu Abstract. Question answering for Machine reading evaluation track is a aim to check machine understanding ability of a machine. As we analyzed most crusial part for efficient working of this system is to select text which needs to be considered for understanding … All 3 versions
Using Anaphora resolution in a Question Answering system for Machine Reading Evaluation A Iftene, A Moruz, E Ignat – ims-sites.dei.unipd.it Abstract. This paper describes UAIC1’s Question Answering for Machine Reading Evaluation systems participating in the QA4MRE 2013 evaluation task. We submitted two types of runs, both type of runs based on our system from 2012 edition of QA4MRE, and … Cited by 2 Related articles
Never-Ending Knowledge Base Expansion Through Continuous Machine Reading PH Barchi, ER Hruschka Jr – openreview.net ABSTRACT The automatic information extraction (IE) is one of the main tools for building large scale knowledge bases (KB), because it makes use of this crucial resource to human knowledge record-the text. This work aims to continually expand the KB of the intelligent … Related articles
Bayesian Logic Programs for plan recognition and machine reading S Vijaya Raghavan – 2012 – repositories.lib.utexas.edu Abstract: Several real world tasks involve data that is uncertain and relational in nature. Traditional approaches like first-order logic and probabilistic models either deal with structured data or uncertainty, but not both. To address these limitations, statistical … Related articles All 4 versions
Bulgarian Question Answering for Machine Reading. K Simov, P Osenova, G Georgiev… – … Working Notes/Labs …, 2012 – ims-sites.dei.unipd.it Abstract. In the CLEF 2012 the BulTreeBank Group of LMD, IICT, BAS is participating for QA4MRE task for Bulgarian. The system represented in the paper exploits an NLP Pipeline for Bulgarian in order to process the questions, answers and the supporting texts. Then we … Related articles All 3 versions
Machine Reading for Notion-Based Sentiment Mining R Hobeica, H Hajj, W El Hajj – Data Mining Workshops (ICDMW …, 2011 – ieeexplore.ieee.org Abstract—Although several sentiment classification methods have been proposed, rare are the ones that provide a solid link between human analysis of a sentiment text and machine analysis of the same text. In this paper, we investigate the automation of human’s reading … Related articles All 8 versions
Question Answering for Machine Reading Evaluation on Romanian and English A Iftene, AL Gînsc?, A Moruz, D Trandab??… – ims-sites.dei.unipd.it Abstract. This paper describes UAIC1’s Question Answering for Machine Reading Evaluation systems participating in the QA4MRE 2011 evaluation task. The system is designed to extract knowledge from large volumes of text and to use this knowledge to … Related articles All 3 versions