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Archive for the ‘Text analytics’ Category

As you may recall last month I announced the line-up for Search Solutions 2017, to be held at BCS London on November 29. I’m pleased to announce that this year we’ll also be offering a Tutorial Programme, which will run the preceding day (Tuesday 28th). The programme consists of three half day-tutorials:

  • 09:30-13:00 Designing Search (Dr. Tony Russell-Rose, UXLabs)
  • 14:00-17:30 Text Analysis with GATE (Diana Maynard, University of Sheffield)
  • 14:00-17:30 Searching the Linked Open Data Cloud (Epaminondas Kapetanios, University of Westminster )

My tutorial is fully booked now, but I’ve appended further details below in case you’re interested in attending a future presentation. Last year I attended Diana’s tutorial on GATE and can highly recommend it as an excellent introduction to the platform and NLP in general. This year I am looking forward to Epaminondas’s tutorial on linked open data – very timely and topical!

Full details of pricing and registration are available on the Search Solutions website. Note that the closing date for bookings is Sunday 26th November. Hope to see you there 🙂

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I am looking for a front end / web developer for a 6-month contract (with possible extension) to work on an Innovate-UK funded project investigating graphical approaches to search strategy formulation. The aim of the project is to develop tools and techniques for search query formulation which can be integrated within a visual framework to deliver a more efficient and intuitive approach to professional search applications.

Requirements

  • Proven working experience in web programming
  • Familiarity with popular JavaScript frameworks such as AngularJS
  • Creative problem-solving skills
  • Ideally experience of migrating existing desktop software applications to the web
  • Prepared to sign an NDA governed by English law.

Responsibilities

  • Write well designed, testable, efficient code by using best software development practices
  • Create user interfaces by using standard Javascript/HTML/CSS practices
  • Integrate data from various back-end services and databases
  • Create and maintain software documentation
  • Maintain awareness of emerging technologies & trends and put them into operation

Salary DOE. Part time working possible. Remote working by negotiation, but candidates will need to attend weekly meetings in London. Further details on request. Principals only please – no subcontractors. Can you recommend anyone?

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Recently I’ve had the privilege of working with colleagues at Lexis Nexis on a variety of projects in the area of artificial intelligence and natural language processing. So I am pleased to share with you the following paper, which has been accepted for presentation at the 16th International Conference on Artificial Intelligence and Law in London next week. It’s co-authored with colleagues Zach Bennett and Kate Farmer.

We’ll be presenting this as part of the demo session on Tuesday afternoon. The paper is just two pages long so it’s quite concise, but we are hoping to submit an extended version to a suitable conference or workshop in due course. In the meantime, comments and feedback welcome 🙂

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When I started the London Text Analytics meetup group some seven years ago, ‘text analytics’ was a term used by few, and understood by even fewer. Apart from a handful of enthusiasts and academics (who preferred the label of “natural language processing” anyway), the field was either overlooked or ignored by most people. Even the advent of “big data” – of which the vast majority was unstructured – did little to change perceptions.

But now, in these days of chatbot-fuelled AI mania, it seems everyone wants to be part of the action. The commercialisation and democratisation of hitherto academic subjects such as AI and machine learning have highlighted a need for practical skills that focus explicitly on the management of unstructured data. Career opportunities have inevitably followed, with job adverts now calling directly for skills in natural language processing and text mining. So the publication of Tom Reamy’s book  “Deep Text: Using Text Analytics to Conquer Information Overload, Get Real Value from Social Media, and Add Bigger Text to Big Data” is indeed well timed.

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5126030385_e67759eb7f_zUnless you’ve been on another planet for the last year or so, you‘ll almost certainly have noticed that chatbots (and conversational agents in general) became quite popular during the course of 2016. It seems that every day a new start up or bot framework was launched, no doubt fuelled at least in part by a growth in the application of data science to language data, combined with a growing awareness in machine learning and AI techniques more generally. So it’s not surprising that we now see on a daily basis all manner of commentary on various aspects of chatbots, from marketing to design, development, commercialisation, etc.

But one topic that doesn’t seem to have received quite as much attention is that of evaluation. It seems that in our collective haste to join the chatbot party, we risk overlooking a key question: how do we know when the efforts we have invested in design and development have actually succeeded? What kind of metrics should be applied, and what constitutes success for a chatbot anyway?

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After a brief hiatus, I’m pleased to say that we will shortly be relaunching the London Text Analytics meetup. As many of you know, in the recent past we have organized some relatively large and ambitious events at a variety of locations. But we have struggled to find a regular venue, and as a result have had difficulty in maintaining a scheduled programme of events.

What we really need is a venue we can use on a more regular schedule, ideally on an ex-gratia basis. It doesn’t have to be huge – in fact; a programme of smaller (but more frequent) meetups is in many ways preferable to a handful of big gatherings.

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Here’s a sample of some of the things we’re working on at UXLabs this year, neatly packaged into Masters level ‘internships’. I use quotes there as it’s a convenient term used by many of my academic colleagues, but these opportunities are (a) unpaid and (b) remote (i.e. hosted by your own institution). So perhaps ‘co-supervised MSc projects initiated by a commercial partner’ is more accurate term… Anyway, what we offer is support, expertise, supervision and access to real world data/challenges. If you are interested in working with us on the challenges below, get in touch. (more…)

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