Evaluating the usability of natural language query languages and interfaces to Semantic Web knowledge bases

The need to make the contents of the Semantic Web accessible to end-users becomes increasingly pressing as the amount of information stored in ontology-based knowledge bases steadily increases. Natural language interfaces (NLIs) provide a familiar and convenient means of query access to Semantic Web data for casual end-users. While several studies have shown that NLIs can achieve high retrieval performance as well as domain independence, this paper focuses on usability and investigates if NLIs and natural language query languages are useful from an end-user's point of view. To that end, we introduce four interfaces each allowing a different query language and present a usability study benchmarking these interfaces. The results of the study reveal a clear preference for full natural language query sentences with a limited set of sentence beginnings over keywords or formal query languages. NLIs to ontology-based knowledge bases can, therefore, be considered to be useful for casual or occasional end-users. As such, the overarching contribution is one step towards the theoretical vision of the Semantic Web becoming reality.     

Kaleidoscope: a cooperative menu-guided query interface (SQLversion)

Kaleidoscope's approach is presented in the context of seeking improvement in the usability of interactive structured query language (SQL) interfaces. The system's cooperation is summarized as proposing valid query constituents step-by-step and providing lexical and semantic feedback immediately to users. To implement this intraquery guidance, the context-free grammar (CFG) is extended to capture the constraints useful for intraquery guidance, and the knowledge useful for pruning nonsensical queries and providing semantic feedback is articulated. For the SQL interface, this knowledge includes a strong domain concept, functional dependency, and integrity constraint rules, which can be acquired once in the database design step. The same types of knowledge are useful both for postquery cooperation and intraquery guidance. As SQL is supported bv virtually all database management system (DBMS) vendors, the approach presents a practical solution for casual database access     

DATAPLAN: An interface generator for database semantics

A model system ( called DATAPLAN) is proposed for generation, access, and control of a shared database by casual users in their own terminology. The DATAPLAN system achieves this goal by planning a dialog which hierarchically defines the possible universe of discourse where casual users can communicate with the database. The plan is executed on the domains of hierarchical semantics, and controlled by pattern matching with a goal and generative backtracking mechanism. To ensure flexible and smooth communication of casual users with the shared database, the system generates individualized user class “fuzzy” interfaces. They are composed of multiplex associations of the attributes and values of the shared database with those of casual user classes in varying degrees.     

Dataplan: An interface generator for database semantics

A model system (called DATAPLAN) is proposed for generation, access, and control of a shared database by casual users in their own terminology. The DATAPLAN system achieves this goal by planning a dialog which hierarchically defines the possible universe of discourse where casual users can communicate with the database. The plan is executed on the domains of hierarchical semantics, and controlled by pattern matching with a goal and generative backtracking mechanism. To ensure flexible and smooth communication of casual users with the shared database, the system generates individualized user class “fuzzy” interfaces. They are composed of multiplex associations of the attributes and values of the shared database with those of casual user classes in varying degrees.     

Analogical Problem Solving in Casual and Experienced Users: When Interface Consistency Leads to Inappropriate Transfer

ABSTRACT

The problem-solving abilities of casual users were compared to experienced users in a computer setting. It was hypothesized that casual users would benefit from reduced consistency with other applications. Experience was gauged with a questionnaire and empirical measures. Four interfaces were developed with varying degrees of similarity to Web browsers. Using a Web browser as a source problem, participants were tested with two of the experimental interfaces. The data indicated that the accuracy of casual users was equivalent across consistent and inconsistent interfaces but that the consistent interfaces had significantly higher latencies. The primary conclusions of the study are that performance for casual users is improved by superficially inconsistent interfaces and that their performance is equivalent to experienced users when a true analogue is present. Commonalities with familiar elements may be a hindrance.     

What we know about dyslexia and Web accessibility: a research review

Compared to the online interaction behavior of other users, little is known about the difficulties dyslexic Web users encounter online. This paper reviews existing literature at the intersection of dyslexia and accessibility research to determine what useful knowledge exists regarding this important and relatively large group of users. This review uncovers that, although there are few published usability tests with dyslexic users, there is a considerable body of knowledge on dyslexia as well as many design guidelines for authoring dyslexic-accessible interfaces. Through a comparison of existing accessibility guidelines for dyslexic and non-dyslexic users and discussion of the plain language movement, it is argued that dyslexic-accessible practices may redress difficulties encountered by all Internet users. This conclusion suggests that usability testing yielding a clearer profile of the dyslexic user would further inform the practice of universal design, but also that enough knowledge is already available to allow doing more to increase accessibility for dyslexic Internet users.     

On the pitfalls of bibliographic database searching: comparing successful and less successful users

This article investigates individual factors that determine success and failure in bibliographic database searching. In line with previous research, we hypothesised that the low usability of advanced bibliographic database interfaces (e.g. OvidSP?) would hinder students in implementing their information-seeking knowledge. Furthermore, we assumed high conscientiousness and need for cognitive closure to drive students towards rigidly using such advanced interfaces, even if they overtax them. In a study with 116 psychology undergraduates, 3 types of searchers were identified by means of a cluster analysis: successful database users, unsuccessful database users, and no-database users (e.g. Google Scholar? searchers). Multiple regression revealed the relationship between information-seeking knowledge and search success to be positive for no-database users and negative for unsuccessful database users: unsuccessful database users do not only have trouble putting their information-seeking knowledge into practice; high information-seeking knowledge even impairs their search success, presumably because it makes them use advanced functions that they are not yet able to master. T-tests revealed that unsuccessful users differ from successful users in terms of higher conscientiousness and need for cognitive closure. In conclusion, our results highlight the importance of enhancing database interface usability and underline the crucial role of practical database instruction.     

A data management strategy for transportable natural language interfaces

By transportability of a natural language interface (NLI) we mean the ease with which it can be customized to a new domain and database by the database administrator as opposed to a linguistic expert. Next-generation database systems (Genesis, Exodus, Starburst) are expansible to support a variety of applications each of which may use a different knowledge representation strategy. an enhanced architecture for natural language interfaces is presented that takes advantage of expansible next-generation database systems to facilitate transportability. A two-pass strategy for transportability is required within the enhanced architecture. On the first pass the NLI builds a representation space to facilitate its own transportability. On the second pass a transportability solution (viewed as a learning task) occurs in that representation space. © 1995 John Wiley & Sons, Inc.     

An analysis of the use of natural language processing systems in business

Abstract

The results of a survey conducted amongst managers, users and application developers of Natural Language interrogation systems are presented and analysed. Those that were able to develop successful and effective applications using natural language paid careful attention to the certain stages. It is proposed that these stages are: 1. Systematic analysis of the company's requirements. 2. Effective integration of the natural language technology with the target database ensuring current applications are not adversely affected. 3. Introduction to new users of the system. This resulted in realistic user expectations and enabled effective use of the natural language software. The advantages and disadvantages of natural language interfaces from an application developer, manager and user perspective are also discussed and recommendations made.     

Datenbank-DIALOG: how to communicate with your database in German (and enjoy it)

The paper discusses the requirements for practical natural language interfaces (NLIs), claiming that acceptance is not only based on the linguistic capabilities of a system but on other features as well, particularly portability and ease of handling. It is shown how these features have been realised in Datenbank-DIALOG^*, a German language interface to relational databases. After a brief look at the linguistic capabilities of Datenbank-DIALOG we demonstrate our approach towards a portable and easy-to-handle system. We also show the dependability of the solutions on the design of the core system. The aspects mentioned have rarely been treated in the technical literature, furthermore it is their combination and interaction that makes Datanbank-DIALOG a suitable device for casual users of databases.     

An analysis of the use of natural language processing systems in business

. The results of a survey conducted amongst managers, users and application developers of Natural Language interrogation systems are presented and analysed. Those that were able to develop successful and effective applications using natural language paid careful attention to the certain stages. It is proposed that these stages are: 1. Systematic analysis of the company's requirements. 2. Effective integration of the natural language technology with the target database ensuring current applications are not adversely affected. 3. Introduction to new users of the system. This resulted in realistic user expectations and enabled effective use of the natural language software. The advantages and disadvantages of natural language interfaces from an application developer, manager and user perspective are also discussed and recommendations made.     

KDA: a knowledge-based database assistant with a query guidingfacility

A knowledge-based database assistant (KDA) which integrates a natural language query system with a skeleton-based query guiding facility is provided. When a user works with the KDA natural language query system, the query guiding facility can supply several kinds of skeletons to guide users in performing database retrieval tasks. A semantic network model, S-Net, is introduced to represent the knowledge for natural language query processing and skeleton generation. Methods for implementing the system are discussed     

数据库关键字查询技术研究

随着互联网技术与数据库技术的不断发展和相互结合,越来越多的用户需要访问在线数据库来获取各种信息,在该过程中,用户要对数据库中的数据进行查询。因此,用户就必需要掌握一定的结构化查询语言SQL,而且还要对数据库模式有一个认识和了解。但事实上,多数用户并不会使用结构化查询语言,也不了解数据库模式。所以,便产生了一个很自然的用户需求——数据库支持基于关键字的查询,文章主要就是对数据库支持基于关键字的查询进行简要的分析和探讨。     

A note on human factors issues of natural language interaction with database systems

Efforts at constructing natural language computer systems have turned to implementing database query facilities. If the application domain is limited there is renewed hope for the success of natural language interfaces. This paper reviews arguments for and against such facilities, stresses research in human semantic knowledge, and emphasizes controlled psychologically oriented experimentation. The results of recent experiments are reported.     

INDIANA: An interactive system for assisting database exploration

We propose INDIANA, a system conceived to support a novel paradigm of database exploration. INDIANA assists the users who are interested in gaining insights about a database though an interactive and incremental process, like a conversation that does not happen in natural language. During this process, the system iteratively provides the user with some features of the data that might be “interesting” from the statistical viewpoint, receiving some feedbacks that are later used by the system to refine the features provided to the user in the next step. A key ability of INDIANA is to assist “data enthusiastic” users (i.e., inexperienced or casual users) in the exploration of transactional databases in an interactive way. For this purpose, we develop a number of novel, statistically-grounded algorithms to support the interactive exploration of the database. We report an in-depth experimental evaluation to show that the proposed system guarantees a very good trade-off between accuracy and scalability, and a user study that supports the claim that the system is effective in real-world database-exploration tasks.     

基于语音和笔的手写数学公式纠错方法

采用识别技术的用户界面往往由于识别率的限制容易出错,如何为这类界面提供自然高效的纠错方法十分重要.手写数学公式具有二维结构,难以识别和纠错.提出一种用于纠正手写数学公式识别错误的多通道技术.它允许用户使用笔纠正切分错误,用笔和语音纠正符号识别和表达式结构分析错误.该技术的核心是一个多通道融合算法.融合算法以笔选择的符号和语音作为输入,根据语音输入的类型是数学术语或者数学符号分别选择融合方法,最后修正手写公式并输出最有可能的识别结果.实验结果表明,该技术能有效地纠正手写数学公式识别中的错误,它比基于笔的单通道纠错技术更加高效.     

TORUS: A step towards bridging the gap between data bases and the casual user

This paper describes TORUS, a natural language understanding system that serves as a front end to a data base management system in order to facilitate communication with casual users. The system employs a semantic network to store knowledge about a data base of student files. This knowledge is used to find the meaning of each input statement, to decide what action to take with respect to the data base, and to select information that must be output in response to the input statement. A prototype version of TORUS has been implemented.     

Automated Query Formulation Using an Entity–Relationship Conceptual Schema

Significant effort is expended in developing a high-level conceptual schema for a relational database. However, criticalknowledge is often discarded when the conceptual schema is mapped to aset of relation schemas. As a result, designers and users must employsparser logical-level knowledge to access data. Unfortunately, naiveusers do not possess the detailed logical-level knowledge required toformulate queries corresponding to ad hoc requests. Auniversal relation interface can shield users from underlyingdesign details. However, most universal relation systems have beenbased on abstractions not typically used by database designers.Consequently, the usefulness of these interfaces has been limited.This article demonstrates how an Entity-Relationship (ER) conceptualschema can be used by a high-level interface to formulate queriesautomatically. The notion of contextsis introduced to describethe segmentation of an ER conceptual schema into overlapping subgraphsthat correspond to sets of relations that can be joined in a losslessmanner. Given a set of contexts, natural join query formulation isstraightforward. As demonstrated with a case study using theprototype QUICK system, the techniques presented facilitate theconstruction of high-level, intelligent interfaces.     

A collaborative behavior-based approach for handling ambiguity, uncertainty, and vagueness in robot natural language interfaces

Service robots are used by ordinary people in their houses and offices. For such users, a desirable way to communicate with robots is through natural language interfaces. So far, techniques for developing robot natural language interfaces are far from mature. A major challenge is handling ambiguity, uncertainty, and vagueness in parsing, object resolution, and vague natural language words. In this research, we develop a new approach called the collaborative behavior-based approach, in which behaviors of robots and behaviors of human users, as well as the changes of object states caused by the behaviors, are taken into consideration integratedly in processing natural language user instructions. In this paper, we analyze the special features of a human–robot interface that may affect language understanding, describe our approach that is designed based on the features, and present the implementation and some experimental results.