12,823 research outputs found
Knowledge Rich Natural Language Queries over Structured Biological Databases
Increasingly, keyword, natural language and NoSQL queries are being used for
information retrieval from traditional as well as non-traditional databases
such as web, document, image, GIS, legal, and health databases. While their
popularity are undeniable for obvious reasons, their engineering is far from
simple. In most part, semantics and intent preserving mapping of a well
understood natural language query expressed over a structured database schema
to a structured query language is still a difficult task, and research to tame
the complexity is intense. In this paper, we propose a multi-level
knowledge-based middleware to facilitate such mappings that separate the
conceptual level from the physical level. We augment these multi-level
abstractions with a concept reasoner and a query strategy engine to dynamically
link arbitrary natural language querying to well defined structured queries. We
demonstrate the feasibility of our approach by presenting a Datalog based
prototype system, called BioSmart, that can compute responses to arbitrary
natural language queries over arbitrary databases once a syntactic
classification of the natural language query is made
Uniform: The Form Validation Language
Digital forms are becoming increasingly more prevalent but the ease of creation is not. Web Forms are difficult to produce and validate. This design project seeks to simplify this process. This project is comprised of two parts: a logical programming language (Uniform) and a web application.
Uniform is a language that allows its users to define logical relationships between web elements and apply simple rules to individual inputs to both validate the form and manipulate its components depending on user input. Uniform provides an extra layer of abstraction to complex coding.
The web app implements Uniform to provide business-level programmers with an interface to build and manage forms. Users will create form templates, manage form instances, and cooperatively complete forms through the web app.
Uniform’s development is ongoing, it will receive continued support and is available as open-source. The web application is software owned and maintained by HP Inc. which will be developed further before going to market
OmniFill: Domain-Agnostic Form Filling Suggestions Using Multi-Faceted Context
Predictive suggestion systems offer contextually-relevant text entry
completions. Existing approaches, like autofill, often excel in
narrowly-defined domains but fail to generalize to arbitrary workflows. We
introduce a conceptual framework to analyze the compound demands of a
particular suggestion context, yielding unique opportunities for large language
models (LLMs) to infer suggestions for a wide range of domain-agnostic
form-filling tasks that were out of reach with prior approaches. We explore
these opportunities in OmniFill, a prototype that collects multi-faceted
context including browsing and text entry activity to construct an LLM prompt
that offers suggestions in situ for arbitrary structured text entry interfaces.
Through a user study with 18 participants, we found that OmniFill offered
valuable suggestions and we identified four themes that characterize users'
behavior and attitudes: an "opportunistic scrapbooking" approach; a trust
placed in the system; value in partial success; and a need for visibility into
prompt context.Comment: 14 pages, 5 figure
From the web of data to a world of action
This is the author’s version of a work that was accepted for publication in Web Semantics: Science, Services and Agents on the World Wide Web. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Web Semantics: Science, Services and Agents on the World Wide Web 8.4
(2010): 10.1016/j.websem.2010.04.007This paper takes as its premise that the web is a place of action, not just information, and that the purpose of
global data is to serve human needs. The paper presents several component technologies, which together work
towards a vision where many small micro-applications can be threaded together using automated assistance to
enable a unified and rich interaction. These technologies include data detector technology to enable any text to
become a start point of semantic interaction; annotations for web-based services so that they can link data to
potential actions; spreading activation over personal ontologies, to allow modelling of context; algorithms for
automatically inferring 'typing' of web-form input data based on previous user inputs; and early work on inferring
task structures from action traces. Some of these have already been integrated within an experimental web-based
(extended) bookmarking tool, Snip!t, and a prototype desktop application On Time, and the paper discusses how the
components could be more fully, yet more openly, linked in terms of both architecture and interaction. As well as
contributing to the goal of an action and activity-focused web, the work also exposes a number of broader issues,
theoretical, practical, social and economic, for the Semantic Web.Parts of this work were supported by the Information
Society Technologies (IST) Program of the European
Commission as part of the DELOS Network of
Excellence on Digital Libraries (Contract G038-
507618). Thanks also to Emanuele Tracanna, Marco
Piva, and Raffaele Giuliano for their work on On
Time
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