Natural Language processing
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Natural Language processing
How can computers handle human language. Linguistic theory and research. What are the latest discoveries about languages. Latest research discoveries.
Curated by Mariana Soffer
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Barking From the Margins: On écriture féminine

Barking From the Margins: On écriture féminine | Natural Language processing | Scoop.it

May 20, 2011. I’m at an academic conference in Paris. A graduate student gives a paper on a novel about partition by the Pakistani writer Bapsi Sidhwa, making what seems to me to be an innocuous yet perceptive argument on the vexing ways in which gender and colonialism intersect in the novel. During the discussion period, the student is dressed down by the two (female) faculty members chairing the panel. ‘Do you really think Sidhwa has anything to say about partition that’s different from Salman Rushdie just because she’s a woman?’ The student is silent. ‘Don’t work only on women’s writing,’ one professor, a placid blond with an immobile page boy haircut counsels her. ‘That goes for all of you,’ she says. ‘It’s been done, and by people much older than you. It’s over. Find something else to work on.’


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Textopoly

Textopoly | Natural Language processing | Scoop.it
Mariana Soffer's insight:

Textopoly is a virtual space creation to revisit new forms of writing. The site looks like an infinite map where you can write and create texts, post images and sounds.

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A Web Research Corpus Annotated with Freebase Concepts

A Web Research Corpus Annotated with Freebase Concepts | Natural Language processing | Scoop.it
Mariana Soffer's insight:

When you type in a search query -- perhaps Plato -- are you interested in the string of letters you typed? Or the concept or entity represented by that string? But knowing that the string represents something real and meaningful only gets you so far in computational linguistics or information retrieval -- you have to know what the string actually refers to. The Knowledge Graph and Freebase are databases of things, not strings, and references to them let you operate in the realm of concepts and entities rather than strings and n-grams.

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NLP Programming Tutorial

NLP Programming Tutorial | Natural Language processing | Scoop.it

This page contains some of the slides that I've made for tutorials, etc., generally aimed at the Masters or early PhD students in our lab. If you have any questions, corrections, or comments I'd be glad to hear them. If you'd like me to present on these (or something similar), send me an email, I like doing tutorials!

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          CONTENTTutorial 0: Programming BasicsTutorial 1: Unigram Language ModelsTutorial 2: Bigram Language ModelsTutorial 3: The Perceptron AlgorithmTutorial 4: Word SegmentationTutorial 5: Part-of-Speech Tagging with Hidden Markov ModelsTutorial 6: Kana-Kanji Conversion for Japanese InputTutorial 7: Topic ModelsTutorial 8: Phrase Structure ParsingTutorial 9: Advanced Discriminative TrainingTutorial 10: Neural NetworksTutorial 11: Structured PerceptronTutorial 12: Dependency ParsingTutorial 13: Search Algorithms
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On Awareness and Awarenesses - Roslyn Young

On Awareness and Awarenesses - Roslyn Young | Natural Language processing | Scoop.it
On Awareness and Awarenesses - Roslyn Young
Mariana Soffer's insight:

Tests and analysis to determine the best display selection techniques for a computer-aided text-manipulation system reveal that the choice does not hinge on the inherent differences in target-selection speed and accuracy between the different selection devices. Of more importance are such factors as the mix of other operations required of the select-operation hand, the ease of getting the hand to and gaining control of a given selection device, or the fatique effects of its associated operating posture. Besides a light pen, several cursor-controlling devices were tested, including a joystick and an SRI-developed device known as a "mouse." The study was aimed directly at finding the best display selection means for our own text-manipulation system but generalizations applicable to other types of on-line systems were derived.


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Narrative environments: how do they matter?

Narrative environments: how do they matter? | Natural Language processing | Scoop.it

The significance and possible senses of the phrase ‘narrative environment’ are explored. It is argued that ‘narrative environment’ is not only polysemous but also paradoxical; not only representational but also performative; and not just performatively repetitive but also reflexive and constitutive. As such, it is useful for understanding the world of the early 21st century. Thus, while the phrase narrative environment can be used to denote highly capitalised, highly regulated corporate forms, i.e. “brandscapes", it can also be understood as a metaphor for the emerging reflexive knowledge-work-places in the ouroboric, paradoxical economies of the 21stcentury. Narrative environments are the media and the materialities through which we come to comprehend that world and to act in those economies. Narrative environments are therefore, sophistically, performative-representative both of the corporate dominance of life worlds and of the undoing of that dominance, through the iterative responses to the paradoxical injunction: “learn to live".

Note

In the Exordium to Specters of Marx, Derrida examines the phrase “to learn to live". A “strange watchword", he calls it, and yet, he continues, "…nothing is more necessary than this wisdom. It is ethics itself: to learn to live. Life does not know how to live otherwise. And does one ever do anything else but learn to live, alone, from oneself, by oneself? This is, therefore, a strange commitment, both impossible and necessary, for a living being supposed to be alive: “I would like to learn to live."" (Derrida, 1994: xviii)

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Language and Reality

Language and Reality | Natural Language processing | Scoop.it

to the memory of Caleb Gattegno 1911-1988

 

The infinite productions of language mirror the innumerable states of the world; the more we talk about the world, the more the world talks back to us, further unravelling eddies of complexities. But mirror here is a bit deceptive, for words and worlds are intertwined, so intimately entangled to be at times undistinguishable. 

 

Mariana Soffer's insight:

Yet, 'in the beginning, there were no words' (CG), and the world is circumscribed by the oval of a plate with two holes —the face of a parent heavenly floating over the newborn infant. Over the years, language capacity and states of affairs grow out of their reciprocal and evermore personal engagements, to evolve into a supremely integrated system as they partake so to speak of the same flesh. The grasp —hands & words, one has of the world houses the world one lives in; language is the house.

We may then ask —this will be the theme of the lecture, what happens when this delicate and intimate cooperation is thrown off balance, when, for example, the rules of hospitality change; for example, but not only there, in the context of foreign language study: As the student prepares to take the first steps into the foreign language —inventing it along its discovery, a curtain ofsilence cancels the world. What then to chart the course?




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Popular tennis match data. Brought to you by Wimbledon Insights

Popular tennis match data. Brought to you by Wimbledon Insights | Natural Language processing | Scoop.it
Current affairs, world politics, the arts and more from Britain's award-winning magazine
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IBM’s social sentiment analytics track how players are being perceived on Twitter throughout the match, watching not just the number of their tweets but their content, using sophisticated tools to decide what percentage is positive or negative. Ferrer began the match with a positive sentiment score of 83%, with Del Potro trailing at 79%. Then disaster struck. Del Potro fell badly in the very first game, aggravating an existing knee injury.

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Speech of two cultures

Speech of two cultures | Natural Language processing | Scoop.it

The organization of taking turns to talk is fundamental to conversation, as well as to other speech-exchange systems. A model for the turn-taking organization for conversation is proposed, and is examined for its compatibility with a list of grossly observable facts about conversation. The results of the examination suggest that, at least, a model for turn-taking in conversation will be characterized as locally-managed, party-administered, interactionally controlled, and sensitive to recipient design. Several general consequences of the model are explicated, and contrasts are sketched with turn-taking organizations for other speech-exchange systems.

 

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We've lost that lovin' feelin' - Idibon

We've lost that lovin' feelin' - Idibon | Natural Language processing | Scoop.it

 

One of the building blocks of language technology is named entity recognition: identifying the proper nouns and names of real-world items. For people and locations, it’s pretty easy. For organizations and products it gets a bit more ambiguous, since organizations and products often take their names from everyday items (e.g., apple). But the hardest entities to identify are titles.

We report findings from an analysis of top US song titles from 1890-2012. "Love" isn't what it used to be.

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Building data science teams

Building data science teams | Natural Language processing | Scoop.it
A data science team needs people with the right skills and perspectives, and it also requires strong tools, processes, and interaction between the team and the rest of the company.

Via luiy
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luiy's curator insight, June 28, 2013 5:34 PM

Starting in 2008, Jeff Hammerbacher(@hackingdata) and I sat down to share our experiences building the data and analytics groups at Facebook and LinkedIn. In many ways, that meeting was the start of data science as a distinct professional specialization (see the “What makes a data scientist” section of this report for the story on how we came up with the title “Data Scientist”). Since then, data science has taken on a life of its own. The hugely positive response to “What Is Data Science?,” a great introduction to the meaning of data science in today’s world, showed that we were at the start of a movement. There are now regular meetups, well-established startups, and even college curricula focusing on data science. AsMcKinsey’s big data research report and LinkedIn’s data indicates, data science talent is in high demand.

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Why can't the world have a universal language?

Why can't the world have a universal language? | Natural Language processing | Scoop.it
Marc Ettlinger's answer: To answer this question we need to consider why we have multiple languages in the first place.

Presumably at some point, about 100,000-200,000 years ago, Homo Sapiens started using language in the way we mean language now.
Mariana Soffer's insight:

Interesting to think about how language changes prolifically even though what language represents often doesn’t change. I’ll have to think about that, re: diffraction of private experience into public spacetime. The cognitve level is more generic than the emotional level of expression – a more impersonal aesthetic.  Ironically, the intent is to make gesture more enduring and objective, yet the result is more changes over time and space, while the language of gesture is more universal. Of course, verbal expression offers many more advantages through its motility through public media.

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luiy's curator insight, June 10, 2013 3:16 PM

This is where part two of the answer comes in. Language is not simply a means for communicating. Language is also identity. We know that people communicate more than ideas with their language, they communicate who they are, what they believe and where they're from. Subconsciously. So the obstacles to one language are similar to the obstacle to us all wearing the same clothes. It would certainly be cheaper and more efficient, but it's not how people behave. And we see that empirically in studies of how Americans' accents have not homogenized with the advent of TV (Why do some people not have accents?).

Mariana Soffer's comment, June 14, 2013 1:35 AM
Luly thanks a lot for you great insight, I mostly agree
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The Afterlife Ethnographic Survey

The Afterlife Ethnographic Survey | Natural Language processing | Scoop.it

Franz Boas has a facebook page, whose contents suggest that his acumen is undimmed by death. A couple of weeks ago, one of his facebook friends asked this:


Via Andrea Naranjo
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Dadameter

Dadameter | Natural Language processing | Scoop.it
Mariana Soffer's insight:

Imagine a world of transparency where all desires are negotiated on a global market and their risks are evaluated and optimized.

 

The Dadameter is a tool for the profiling of language at large scale and the historical tracking of artistic and literary movements. It brings about a new alliance between art, science and global finance.

 

We use up-to-date 2.0 trend analysis and data visualization technologies, neural networks, graph theory or quantitative structural linguistics in order to be able to predict the next artistic craze.

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The Language of Art, by Paul Rand

The Language of Art, by Paul Rand | Natural Language processing | Scoop.it
My introduction to the field of design came when I stumbled upon one of Paul Rand's books while I was an undergrad at MIT. It was a little over a decade later when I had the fortune of meeting Mr. ...
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The History of Typography, in Stop-Motion Animation

The History of Typography, in Stop-Motion Animation | Natural Language processing | Scoop.it

Fonts and typefaces have officially become a mainstream obsession. In our current design-centric culture, terms like sans-serif, Helvetica, and — heaven forbid — Comic Sans have breached the cultural consciousness.

 

Fortunately, for those of you who still can’t tell your Futura from your Papyrus, Yukon-based designer Ben Barrett-Forrest has crafted this charming stop-motion history lesson to help you get up to speed.

Built with 2454 photographs, 291 letters, and 140 hours of his life, Barrett-Forrest’s animated short is a delight . As he guides us from the lowly beginnings of Guttenberg’s printing press, all the way to the computer age, it becomes apparent that the art of type is a corollary for history. Like architecture and fashion, typography is a reflection of the world in which it’s created. Barrett-Forrest explains his interest in type and the genesis of the project in an interview at the article link.


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How Does Writing Affect Your Brain? [infographic]

How Does Writing Affect Your Brain? [infographic] | Natural Language processing | Scoop.it
Today’s infographic informs us that storytellers have the power to “plant emotions, thoughts, and ideas into the brain of the listener.”

Via Jan Bergmans
Mariana Soffer's insight:

Most of us write a little something everyday. It might be a grocery list, a poem, or a write-up on the infographic of the day. As we go through this daily ritual, however, we are probably not aware of the effects writing has on our brains.

According to today’s infographic, writing can serve as a calming, meditative tool. Stream of conscious writing exercises, in particular, have been identified as helpful stress coping methods. Keeping a journal, for example, or trying out free-writing exercises, can drastically reduce your levels of stress.

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Jan Bergmans's curator insight, July 11, 2013 3:35 AM

 

a new infographic every day

HomeAboutContactSitemapCategories »How Does Writing Affect Your Brain? [infographic]May 26, 2013 |  by Micaela Lacy  |  Education, Health, Mind-Blowing

Most of us write a little something everyday. It might be a grocery list, a poem, or a write-up on the infographic of the day. As we go through this daily ritual, however, we are probably not aware of the effects writing has on our brains.

According to today’s infographic, writing can serve as a calming, meditative tool. Stream of conscious writing exercises, in particular, have been identified as helpful stress coping methods. Keeping a journal, for example, or trying out free-writing exercises, can drastically reduce your levels of stress.

It should also be noted that writing can hold a powerful influence over its readers. Today’s infographic informs us that storytellers have the power to “plant emotions, thoughts, and ideas into the brain of the listener.” But all of these mind-shaping tools can be completely disregarded if one chooses to insert a cliché into his or her writing. When you hear phrases like “love is blind” or “dumb blonde,” your brain skips over these ideas and simply accepts them as a collection of words. Clichés have become so familiar to us that the sensory responses they are supposed to evoke are often severely diluted.

So, whether you’re trying to de-stress, or improve your writing, check out the infographic below for some helpful insight into the goings-on of your brain. I hope you never stop writing! [Via]

Sayeed Mohiuddin's curator insight, August 1, 2013 4:48 AM

The more you write the better you remember!

Allan Dale Maurer's curator insight, January 30, 2014 11:29 AM

We think in stories. More than 100 years of multi-disciplinary research shows that narrative is our primary mode of thought and we turn to other methods (scientific, a blueprint, etc.) for specific purposes.

 

 

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Metaphors We Live By George Lakoff, Mark Johnson

Metaphors We Live By George Lakoff, Mark Johnson | Natural Language processing | Scoop.it
Mariana Soffer's insight:

The now-classic Metaphors We Live By changed our understanding of metaphor and its role in language and the mind. Metaphor, the authors explain, is a fundamental mechanism of mind, one that allows us to use what we know about our physical and social experience to provide understanding of countless other subjects. Because such metaphors structure our most basic understandings of our experience, they are "metaphors we live by"—metaphors that can shape our perceptions and actions without our ever noticing them.

In this updated edition of Lakoff and Johnson's influential book, the authors supply an afterword surveying how their theory of metaphor has developed within the cognitive sciences to become central to the contemporary understanding of how we think and how we express our thoughts in language.

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Steven Pinker on Metaphor and the Mind

Steven Pinker on Metaphor and the Mind | Natural Language processing | Scoop.it
I think that metaphor really is a key to explaining thought and language. The human mind comes equipped with an ability to penetrate the cladding of sensory appearance and discern the abstract construction underneath - not always on demand, and not infallibly, but often enough and insightfully enough to shape the human condition. 

Our powers of analogy allow us to apply ancient neural structures to newfound subject matter, to discover hidden laws and systems in nature, and not least, to amplify the expressive power of language itself.
Mariana Soffer's insight:
 Steven Pinker, Canadian-American experimental psychologist, cognitive scientist and linguist, cited in Mariana Soffer, Metaphor and the Mind, Sing your own lullaby (via amiquote) 
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Chat or What: Approaching Text Normalization in Chats and Social Networks

Chat or What: Approaching Text Normalization in Chats and Social Networks | Natural Language processing | Scoop.it
Mariana Soffer's insight:

It is not strange that, with the overload of user-generated content, there is an increasing interest on processing chat/SMS-like language. Social Networks, virtual worlds, MMORPGsand chat rooms are plagued with emoticons, abbreviations, typos and channel codes that make the task of processing user-generated text a nightmare. In this post I list a number of resources and approaches that may be useful for researchers and practitioners of Natural Language Processing

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Lexical facts

Lexical facts | Natural Language processing | Scoop.it

 TestYourVocab.com  reached its two millionth test result, and so the researchers have put together some data:

Most adult native test-takers range from 20,000–35,000 wordsAverage native test-takers of age 8 already know 10,000 wordsAverage native test-takers of age 4 already know 5,000 wordsAdult native test-takers learn almost 1 new word a day until middle ageAdult test-taker vocabulary growth basically stops at middle ageThe most common vocabulary size for foreign test-takers is 4,500 wordsForeign test-takers tend to reach over 10,000 words by living abroadForeign test-takers learn 2.5 new words a day while living in an English-speaking country
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Display-Selection Techniques for Text Manipulation

Display-Selection Techniques for Text Manipulation | Natural Language processing | Scoop.it

 Tests and analysis to determine the best display selection techniques for a computer-aided text-manipulation system reveal that the choice does not hinge on the inherent differences in target-selection speed and accuracy between the different selection devices. Of more importance are such factors as the mix of other operations required of the select-operation hand, the ease of getting the hand to and gaining control of a given selection device, or the fatique effects of its associated operating posture. Besides a light pen, several cursor-controlling devices were tested, including a joystick and an SRI-developed device known as a "mouse." The study was aimed directly at finding the best display selection means for our own text-manipulation system but generalizations applicable to other types of on-line systems were derived.


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Extraction of Main Text Content Using the Google Reader NoAPI

Extraction of Main Text Content Using the Google Reader NoAPI | Natural Language processing | Scoop.it

Extracting the main text content from a web page is an important step in the text processing pipeline. The source code of pages in HTML is usually cluttered with advertising and other text which is not related to the main content. Formally, in the context of computer science, it is impossible for a computer to distinguish between the main content and other content on the same page. That is, no algorithm can recognize it for all possible cases. Sometimes it is even difficult for humans to distinguish it. Recognition of primary content is part of the machine learning/artificial intelligence field of study.

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Symbol Grounding and Symbol Tethering

Symbol Grounding and Symbol Tethering | Natural Language processing | Scoop.it

Philosopher Aaron Sloman claims that symbol grounding is impossible. I say it ispossible, indeed necessary, for strong AI. Yet my own approach may be compatible with Sloman's.

Sloman equates "symbol grounding" withconcept empiricism, thus rendering it impossible. However, I don't see the need to equate all symbol grounding to concept empiricism. And what Sloman calls "symbol tethering" may be what I call "symbol grounding," or at least a type of symbol grounding.


Via Samuel H. Kenyon
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The Storytelling Animal

The Storytelling Animal | Natural Language processing | Scoop.it
Humans live in landscapes of make-believe. We spin fantasies. We devour novels, films, and plays. Even sporting events and criminal trials unfold as narratives. Yet the world of story has long remained an undiscovered and unmapped country.

Via FastTFriend
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aniamaclain's comment, May 16, 2013 5:23 AM
cool
FastTFriend's comment, May 16, 2013 7:47 AM
I think so too.