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Natural-language user interface

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Natural Language User Interfaces (LUI) are a type of computer human interface where linguistic phenomena such as verbs, phrases and clauses act as UI controls for creating, selecting and modifying data in software applications.

In interface design natural language interfaces are sought after for their speed and ease of use, but most suffer the challenges to understanding wide varieties of ambiguous input.[1] Natural language interfaces are an active area of study in the field of natural language processing and Computational linguistics. An intuitive general Natural language interface is one of the active goals of the Semantic Web.

It is important to note that text interfaces are 'natural' to varying degrees, and that many formal (un-natural) programming languages incorporate idioms of natural human language. Likewise, a traditional keyword search engine could be described as a 'shallow' Natural language user interface.

Overview

A natural language search engine would in theory find targeted answers to user questions (as opposed to keyword search). For example, when confronted with a question of the form 'which U.S. state has the highest income tax?', conventional search engines ignore the question and instead do a search on the keywords 'state, income and tax'. Natural language search, on the other hand, attempts to use natural language processing to understand the nature of the question and then to search and return a subset of the web that contains the answer to the question. If it works, results would have a higher relevance than results from a keyword search engine.

From a commercial standpoint, advertising on the results page could also be more relevant and could have a higher revenue potential than that of keyword search engines.[citation needed]

History

Prototype Nl interfaces had already appeared in the late sixties and early seventies.[2]

  • Lunar, a natural language interface to a database containing chemical analyses of Apollo-11 moon rocks by [William Woods http://parsecraft.com/].
  • Chat-80 transformed English questions into Prolog expressions, which were evaluated against the Prolog database. The code of Chat-80 was circulated

widely, and formed the basis of several other experimental Nl interfaces.

  • Janus is also one of the few systems to support temporal questions.
  • Intellect from Trinzic (formed by the merger of AICorp and Aion).
  • Bbn’s Parlance built on experience from the development of the Rus and Irus systems.
  • Ibm’s Languageaccess
  • Q&A from Symantec.
  • Datatalker from Natural Language Inc.
  • Loqui from Bim.
  • English Wizard from Linguistic Technology Corporation.

Applications

Ubiquity

Main article: Ubiquity (Firefox)

Ubiquity, an add-on for Mozilla Firefox, is a collection of quick and easy natural-language-derived commands that act as mashups of web services, thus allowing users to get information and relate it to current and other webpages.

Wolfram Alpha

Main article: Wolfram Alpha

Wolfram Alpha is an online service that answers factual queries directly by computing the answer from structured data, rather than providing a list of documents or web pages that might contain the answer as a search engine would.[3] It was announced in March 2009 by Stephen Wolfram, and was released to the public on May 15, 2009.[4]

Siri

Main article: Siri Personal Assistant

Siri is a personal assistant application for the iPhone OS. The application uses natural language processing to answer questions and make recommendations. The iPhone app is the first public product by its makers, who are focused on artificial intelligence applications.

Siri's marketing claims include that Siri adapts to the user's individual preferences over time and personalizes results, as well as accomplishing tasks such as making dinner reservations while trying to catch a cab.[5]

Others

Challenges

Natural language interfaces have in the past led users to anthropomorphize the computer, or at least to attribute more intelligence than is warranted to it. This leads to unrealistic expectations of the capabilities of the system on the part of the user. Such expectations will make it difficult to learn the restrictions of the system if they attribute too much capability to it, and they will lead to disappointment when the system fails to perform as expected.

A 1995 paper titled 'Natural Language Interfaces to Databases – An Introduction', describes some challenges:[2]

  • Modifier attachment

The request “List all employees in the company with a driving licence” is ambiguous unless you know companies can't have drivers licences.

  • Conjunction and disjunction

“List all applicants who live in California and Arizona.” is ambiguous unless you know that a person can't live in two places at once.

- resolve what a user means by 'he', 'she' or 'it', in a self-referential query.

See also

References

  1. ^ Hill, I. (1983). "Natural language versus computer language." In M. Sime and M. Coombs (Eds.) Designing for Human-Computer Communication. Academic Press.
  2. ^ a b Natural Language Interfaces to Databases – An Introduction, I. Androutsopoulos, G.D. Ritchie, P. Thanisch, Department of Artificial Intelligence, University of Edinburgh
  3. ^ Johnson, Bobbie (2009-03-09). "British search engine 'could rival Google'". The Guardian. Retrieved 2009-03-09.
  4. ^ "So Much for A Quiet Launch". Wolfram Alpha Blog. 2009-05-08. Retrieved 2009-10-20.
  5. ^ Siri homepage
  6. ^ http://www.nytimes.com/reuters/technology/tech-powerset.html?_r=1&oref=slogin[dead link]
  7. ^ Powerset Blog : Microsoft to Acquire Powerset

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