19,813 research outputs found
Natural language processing
Beginning with the basic issues of NLP, this chapter aims to chart the major research activities in this area since the last ARIST Chapter in 1996 (Haas, 1996), including: (i) natural language text processing systems - text summarization, information extraction, information retrieval, etc., including domain-specific applications; (ii) natural language interfaces; (iii) NLP in the context of www and digital libraries ; and (iv) evaluation of NLP systems
Design and evaluation of acceleration strategies for speeding up the development of dialog applications
In this paper, we describe a complete development platform that features different innovative acceleration strategies, not included in any other current platform, that simplify and speed up the definition of the different elements required to design a spoken dialog service. The proposed accelerations are mainly based on using the information from the backend database schema and contents, as well as cumulative information produced throughout the different steps in the design. Thanks to these accelerations, the interaction between the designer and the platform is improved, and in most cases the design is reduced to simple confirmations of the “proposals” that the platform dynamically provides at each step.
In addition, the platform provides several other accelerations such as configurable templates that can be used to define the different tasks in the service or the dialogs to obtain or show information to the user, automatic proposals for the best way to request slot contents from the user (i.e. using mixed-initiative forms or directed forms), an assistant that offers the set of more probable actions required to complete the definition of the different tasks in the application, or another assistant for solving specific modality details such as confirmations of user answers or how to present them the lists of retrieved results after querying the backend database. Additionally, the platform also allows the creation of speech grammars and prompts, database access functions, and the possibility of using mixed initiative and over-answering dialogs. In the paper we also describe in detail each assistant in the platform, emphasizing the different kind of methodologies followed to facilitate the design process at each one.
Finally, we describe the results obtained in both a subjective and an objective evaluation with different designers that confirm the viability, usefulness, and functionality of the proposed accelerations. Thanks to the accelerations, the design time is reduced in more than 56% and the number of keystrokes by 84%
SQL Query Completion for Data Exploration
Within the big data tsunami, relational databases and SQL are still there and
remain mandatory in most of cases for accessing data. On the one hand, SQL is
easy-to-use by non specialists and allows to identify pertinent initial data at
the very beginning of the data exploration process. On the other hand, it is
not always so easy to formulate SQL queries: nowadays, it is more and more
frequent to have several databases available for one application domain, some
of them with hundreds of tables and/or attributes. Identifying the pertinent
conditions to select the desired data, or even identifying relevant attributes
is far from trivial. To make it easier to write SQL queries, we propose the
notion of SQL query completion: given a query, it suggests additional
conditions to be added to its WHERE clause. This completion is semantic, as it
relies on the data from the database, unlike current completion tools that are
mostly syntactic. Since the process can be repeated over and over again --
until the data analyst reaches her data of interest --, SQL query completion
facilitates the exploration of databases. SQL query completion has been
implemented in a SQL editor on top of a database management system. For the
evaluation, two questions need to be studied: first, does the completion speed
up the writing of SQL queries? Second , is the completion easily adopted by
users? A thorough experiment has been conducted on a group of 70 computer
science students divided in two groups (one with the completion and the other
one without) to answer those questions. The results are positive and very
promising
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