Natural-language user interface

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Natural-language user interface (LUI or NLUI) is 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.

Contents

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.

Text interfaces are "natural" to varying degrees. 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 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, due to the question being included.[ citation needed ]

History

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

Challenges

Natural-language interfaces have in the past led users to anthropomorphize the computer, or at least to attribute more intelligence to machines than is warranted. On the part of the user, this has led to unrealistic expectations of the capabilities of the system. Such expectations will make it difficult to learn the restrictions of the system if users attribute too much capability to it, and will ultimately lead to disappointment when the system fails to perform as expected as was the case in the AI winter of the 1970s and 80s.

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 that companies can't have driving 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.
Anaphora resolution
resolve what a user means by 'he', 'she' or 'it', in a self-referential query.

Other goals to consider more generally are the speed and efficiency of the interface, in all algorithms these two points are the main point that will determine if some methods are better than others and therefore have greater success in the market. In addition, localisation across multiple language sites requires extra consideration - this is based on differing sentence structure and language syntax variations between most languages.

Finally, regarding the methods used, the main problem to be solved is creating a general algorithm that can recognize the entire spectrum of different voices, while disregarding nationality, gender or age. The significant differences between the extracted features - even from speakers who says the same word or phrase - must be successfully overcome.

Uses and applications

The natural-language interface gives rise to technology used for many different applications.

Some of the main uses are:

Below are named and defined some of the applications that use natural-language recognition, and so have integrated utilities listed above.

Ubiquity

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

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. [5] It was announced in March 2009 by Stephen Wolfram, and was released to the public on May 15, 2009. [6]

Siri

Siri is an intelligent personal assistant application integrated with operating system iOS. The application uses natural language processing to answer questions and make recommendations.

Siri's marketing claims include that it adapts to a user's individual preferences over time and personalizes results, and performs tasks such as making dinner reservations while trying to catch a cab. [7]

Others

Screenshot of GNOME DO classic interface GNOME Do Classic.png
Screenshot of GNOME DO classic interface

See also

Related Research Articles

Information retrieval (IR) in computing and information science is the process of obtaining information system resources that are relevant to an information need from a collection of those resources. Searches can be based on full-text or other content-based indexing. Information retrieval is the science of searching for information in a document, searching for documents themselves, and also searching for the metadata that describes data, and for databases of texts, images or sounds.

Natural-language understanding (NLU) or natural-language interpretation (NLI) is a subtopic of natural-language processing in artificial intelligence that deals with machine reading comprehension. Natural-language understanding is considered an AI-hard problem.

Question answering (QA) is a computer science discipline within the fields of information retrieval and natural language processing (NLP) that is concerned with building systems that automatically answer questions that are posed by humans in a natural language.

Document retrieval is defined as the matching of some stated user query against a set of free-text records. These records could be any type of mainly unstructured text, such as newspaper articles, real estate records or paragraphs in a manual. User queries can range from multi-sentence full descriptions of an information need to a few words.

<span class="mw-page-title-main">Content-based image retrieval</span> Method of image retrieval

Content-based image retrieval, also known as query by image content (QBIC) and content-based visual information retrieval (CBVIR), is the application of computer vision techniques to the image retrieval problem, that is, the problem of searching for digital images in large databases. Content-based image retrieval is opposed to traditional concept-based approaches.

Lexxe is an internet search engine that applies Natural Language Processing in its semantic search technology. Founded in 2005 by Dr. Hong Liang Qiao, Lexxe is based in Sydney, Australia. Today, Lexxe's key focus is on sentiment search with the launch of a news sentiment search site at News & Moods (www.newsandmoods.com).

<span class="mw-page-title-main">Dialogue system</span>

A dialogue system, or conversational agent (CA), is a computer system intended to converse with a human. Dialogue systems employed one or more of text, speech, graphics, haptics, gestures, and other modes for communication on both the input and output channel.

Search Engine Results Pages (SERP) are the pages displayed by search engines in response to a query by a user. The main component of the SERP is the listing of results that are returned by the search engine in response to a keyword query.

Social search is a behavior of retrieving and searching on a social searching engine that mainly searches user-generated content such as news, videos and images related search queries on social media like Facebook, LinkedIn, Twitter, Instagram and Flickr. It is an enhanced version of web search that combines traditional algorithms. The idea behind social search is that instead of ranking search results purely based on semantic relevance between a query and the results, a social search system also takes into account social relationships between the results and the searcher. The social relationships could be in various forms. For example, in LinkedIn people search engine, the social relationships include social connections between searcher and each result, whether or not they are in the same industries, work for the same companies, belong the same social groups, and go the same schools, etc.

Powerset was an American company based in San Francisco, California, that, in 2006, was developing a natural language search engine for the Internet. On July 1, 2008, Powerset was acquired by Microsoft for an estimated $100 million.

hakia Internet search engine

hakia was an Internet search engine. Launched in March 2004 and based in New York City, hakia attempted to pioneer a semantic search engine in contrast to keyword search engines that were established at that time. The search engine ceased operations in 2014. Since 2015 the domain has been owned by HughesNet.

Barney Pell is an American entrepreneur, angel investor and computer scientist. He was co-founder and CEO of Powerset, a pioneering natural language search startup, search strategist and architect for Microsoft's Bing search engine, a pioneer in the field of general game playing in artificial intelligence, and the architect of the first intelligent agent to fly onboard and control a spacecraft. He was co-founder, Vice Chairman and Chief Strategy Officer of Moon Express; co-founder and chairman of LocoMobi; and Associate Founder of Singularity University.

A concept search is an automated information retrieval method that is used to search electronically stored unstructured text for information that is conceptually similar to the information provided in a search query. In other words, the ideas expressed in the information retrieved in response to a concept search query are relevant to the ideas contained in the text of the query.

Natural-language programming (NLP) is an ontology-assisted way of programming in terms of natural-language sentences, e.g. English. A structured document with Content, sections and subsections for explanations of sentences forms a NLP document, which is actually a computer program. Natural language programming is not to be mixed up with natural language interfacing or voice control where a program is first written and then communicated with through natural language using an interface added on. In NLP the functionality of a program is organised only for the definition of the meaning of sentences. For instance, NLP can be used to represent all the knowledge of an autonomous robot. Having done so, its tasks can be scripted by its users so that the robot can execute them autonomously while keeping to prescribed rules of behaviour as determined by the robot's user. Such robots are called transparent robots as their reasoning is transparent to users and this develops trust in robots. Natural language use and natural-language user interfaces include Inform 7, a natural programming language for making interactive fiction, Shakespeare, an esoteric natural programming language in the style of the plays of William Shakespeare, and Wolfram Alpha, a computational knowledge engine, using natural-language input. Some methods for program synthesis are based on natural-language programming.

Yebol was a vertical "decision" search engine that had developed a knowledge-based, semantic search platform. Based in San Jose, California, Yebol's artificial intelligence human intelligence-infused algorithms automatically cluster and categorize search results, web sites, pages and contents that it presents in a visually indexed format that is more aligned with initial human intent. Yebol used association, ranking and clustering algorithms to analyze related keywords or web pages. Yebol presented as one of its goals the creation of a unique "homepage look" for every possible search term.

The Ubiquitous Knowledge Processing Lab is a research lab at the Department of Computer Science at the Technische Universität Darmstadt. It was founded in 2006 by Iryna Gurevych.

The following outline is provided as an overview of and topical guide to natural-language processing:

Schema-agnostic databases or vocabulary-independent databases aim at supporting users to be abstracted from the representation of the data, supporting the automatic semantic matching between queries and databases. Schema-agnosticism is the property of a database of mapping a query issued with the user terminology and structure, automatically mapping it to the dataset vocabulary.

Query understanding is the process of inferring the intent of a search engine user by extracting semantic meaning from the searcher’s keywords. Query understanding methods generally take place before the search engine retrieves and ranks results. It is related to natural language processing but specifically focused on the understanding of search queries. Query understanding is at the heart of technologies like Amazon Alexa, Apple's Siri. Google Assistant, IBM's Watson, and Microsoft's Cortana.

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. 1 2 Natural Language Interfaces to Databases – An Introduction, I. Androutsopoulos, G.D. Ritchie, P. Thanisch, Department of Artificial Intelligence, University of Edinburgh
  3. ↑ "Chat-80 demo". Archived from the original on 11 November 2016. Retrieved 29 January 2018.
  4. ↑ "ELIZA demo". Archived from the original on 26 November 2016. Retrieved 29 January 2018.
  5. ↑ Johnson, Bobbie (2009-03-09). "British search engine 'could rival Google'". The Guardian . Retrieved 2009-03-09.
  6. ↑ "So Much for A Quiet Launch". Wolfram Alpha Blog. 2009-05-08. Retrieved 2009-10-20.
  7. ↑ "iOS - Siri". Apple. Retrieved 29 January 2018.
  8. ↑ "Braina - Artificial Intelligence Software for Windows". www.brainasoft.com. Retrieved 29 January 2018.
  9. ↑ Ubuntu 10.04 Add/Remove Applications description for GNOME Do
  10. ↑ Helft, Miguel (May 12, 2008). "Powerset Debuts With Search of Wikipedia". The New York Times.
  11. ↑ Johnson, Mark (July 1, 2008). "Microsoft to Acquire Powerset". Powerset Blog. Archived from the original on February 25, 2009.
  12. ↑ Humphries, Matthew. "Yebol.com steps into the search market" Archived 2012-03-15 at the Wayback Machine Geek.com. 31 July 2009.
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