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     

Transportable natural language database update

Natural language database access requires support of both query and update capabilities. Although a great deal of research effort has gone to support natural language database query, little effort has gone to support update. We describe a model of action that supports natural language database update, as well as query, and the implementation of a system that supports the model. A major goal of this research is to design a system that is easily transportable both to different database domains and different database management systems.     

A form-based natural language front-end to a CIM database

The paper presents a methodology for developing a user interface that combines fourth generation interface tools (SQL forms) with a natural language processor for a database management system. The natural language processor consists of an index, a lexicon and a parser. The index is used to uniquely identify each form in the system through a conceptual representation of its purpose. The form fields specify database or nondatabase fields whose values are either entered by the user (user-defined) or are derived by the form (system-defined) in response to user input. A set of grammar rules are associated with each form. The lexicon consists of all words recognized by the system, their grammatical categories, roots, their associations (if any) with database objects and forms. The parser scans, a natural language query to identify a form in a bottom-up fashion. The information requested in the user query is determined in a top-down manner by parsing, through the grammar rules associated with the identified form. Extragrammatical inputs with limited deviations from the grammar rules are supported. Combining a natural language processor with SQL forms allows processing data modification tasks without violating any database integrity constraint, having duplicate records, or entering invalid data. A prototype natural language interface is described as a front-end to an ORACLE database for a computer integrated manufacturing system     

关于自然语言数据库更新模型问题研究

一个完全的自然语言数据库的存取通常需要既支持查询,也需要支持更新。近几年来,在支持自然语言数据库查询问题的研究上虽然已做了很多工作,但在支持自然语言数据库更新问题的研究上所做的工作却甚少。本文介绍了一种支持自然语言数据库更新的现实世界模型,其目的是设计一个易于移植到不同数据库以及不同DBMS上的系统。     

Word segmentation based on database semantics in NChiql

In this paper a novel word-segmentation algorithm is presented to delimit words in CHinese natural language queries in NChiql system,a Chinese natural language query interface to databases.Although there are sizalbe literatures on Chinese segmentation.,they cannot satisfy particular requirements in this system,The novel word-segmentation algorithm is based on the database semantics,namely Semantic Conceptual Model(SCM) for specific domain Knowledge,Based namely Semantic COnceptual Model(SCM) for specific domain knowledge,Based on SCM,the segmenter labels the database semantics to words directly,which eases the disambiguation and translation(from natural language to database query)in NChiql.     

基于自裁剪异构图的NL2SQL模型

自然语言转换为结构化查询语言（NL2SQL）是语义解析领域的重要任务,其核心为对数据库模式和自然语言问句进行联合学习。现有研究通过将整个数据库模式和自然语言问句联合编码构建异构图,使得异构图中引入大量无用信息,并且忽略了数据库模式中不同信息的重要性。为提高NL2SQL模型的逻辑与执行准确率,提出一种基于自裁剪异构图与相对位置注意力机制的NL2SQL模型（SPRELA）。采用序列到序列的框架,使用ELECTRA预训练语言模型作为骨干网络。引入专家知识,对数据库模式和自然语言问句构建初步异构图。基于自然语言问句对初步异构图进行自裁剪,并使用多头相对位置注意力机制编码自裁剪后的数据库模式与自然语言问句。利用树型解码器和预定义的SQL语法,解码生成SQL语句。在Spider数据集上的实验结果表明,SPRELA模型执行准确率达到71.1%,相比于相同参数量级别的RaSaP模型提升了1.1个百分点,能够更好地将数据库模式与自然语言问句对齐,从而理解自然语言查询中的语义信息。     

An overview of cooperative answering

Databases and information systems are often hard to use because they do not explicitly attempt to cooperate with their users. Direct answers to database and knowledge base queries may not always be the best answers. Instead, an answer with extra or alternative information may be more useful and less misleading to a user. This paper surveys foundational work that has been done toward endowing intelligent information systems with the ability to exhibit cooperative behavior. Grice's maxims of cooperative conversation, which provided a starting point for the field of cooperative answering, are presented along with relevant work in natural language dialogue systems, database query answering systems, and logic programming and deductive databases. The paper gives a detailed account of cooperative techniques that have been developed for considering users' beliefs and expectations, presuppositions, and misconceptions. Also, work in intensional answering and generalizing queries and answers is covered. Finally, the Cooperative Answering System at Maryland, which is intended to be a general, portable platform for supporting a wide spectrum of cooperative answering techniques, is described.     

Semantic interpretation of a database query language

In this paper, we will discuss a system that semantically interprets a formal database accessing language and generates natural language from this interpretation. In the past, the major way of communication between a user and a database was by means of a formal language. One such language is the SQL query language. Even though constructed as a user friendly language, SQL exemplifies the same difficulties for users as do other formal languages, namely a fairly rigid syntax, the necessity of variable binding, the lack of pronouns, and in the case of erroneous queries error messages that do not provide much insight. To alleviate some of the formal language problems, yet utilize the power of the formal language, we set out to build a natural language ‘umbrella’ for the SQL user. Our goal was not to build a natural language query system, but rather to use semantic knowledge and natural language for paraphrasing the formal language (SQL) and producing error messages as a feedback mechanism. In this way we build a genuine help facility, which would not only aid the user in dealing with SQL, but also trap erroneous queries.     

An extensible DBMS for small and medium systems

An extensible, relational database management system called Requiem is described that offers users a truly relational interface, and is independent of query language. Requiem (relational query and update interactive system) is an interactive system with facilities for querying and updating a database. The organization of Requiem, the structure of its query language RQL, and the structure of the database are discussed     

TQuery: a context-sensitive temporal query language.

Users of electronic medical databases request pertinent information by recasting their clinical questions into a formal database query language. Because the query language is the user's only access to the data, the query language must be powerful enough to enable users to express their data requirements. However, a competing need is for the query language to be restrictive enough so that queries can have unambiguous semantics and the query processor can generate correct answers. We describe a query language, called TQuery , that was designed specifically to formulate database queries that are dependent on temporal and contextual relationships. TQuery specifications express contextual constraints without the need to explicitly reference calendar dates. TQuery is the database query language used to retrieve patient data from an object-oriented electronic patient medical-record system called the temporal network (TNET). TNET and TQuery were developed to support the real-time temporal reasoning and representation needs of a LISP workstation-based medical expert system.     

中文数据库自然语言查询系统Nchiql设计与实现

中文数据库自然语言查询的研究有两个基本目标,首先解决NLIDB面临的可移植性和可用性的问题,其次提出适合中文自然语言查询处理的特有方法,为此开了了中文数据库自然语言查询系统NChiql,从总体设计的角度,介绍了NChiql中的可移植性体系结构、中文自然语言查询分析、基于数据库语言的自然语言查询分析与转换和智能界面管理等内容,实验表明,该系统具有良好的可用性及高效和鲁棒的语言分析器。     

数据库汉语查询接口WTCDIS系统的设计与实现

数据库自然语言查询接口可以使用户直接以日常生活中使用的自然语言提出查询请求,获取数据库中的信息。这是一个具有重要理论价值和巨大实用价值的研究领域。本文在总结数据库汉语查询的语言规律基础上,重点介绍了我们设计实现的一个数据库汉语查询接口系统WTCDIS,最后给出了对该系统进行初步测试的结果。     

Generating English paraphrases from relational query expressions

Of the many problems facing the casual user of a data-base enquiry system probably the most difficult is gaining a competent understanding of the associated query language. Given that he manages to construct a well-formed query expression there is no guarantee that it exactly reflects the original question. The research described here concerns the design of an interpreter from a formal query language to natural language to aid query verification in a relational data-base environment. The system is being developed to work in conjunction with the ICL Natural Language enquiry interface NEL which translates English query expressions into the formal query language QUERYMASTER. The requirements of a natural-language paraphraser are first discussed and the nature of an intermediate representation is defined and motivated with respect to an applied relational calculus. Consideration is then given to choosing a suitable underlying framework with which to underpin the practical work and the choice of Lexical Functional Grammar as the guiding theory is explained. Finally, the research is set in the context of a longer-term programme to construct a multi-purpose user interface incorporating facilities for handling data-base metaknowledge and query building,     

QQL: A DB&;IR Query Language

Traditional database query languages are based on set theory and crisp first order logic. However, many applications require retrieval-like queries which return result objects associated with a degree of being relevant to the query. Historically, retrieval systems estimate relevance by exploiting hidden object semantics whereas query processing in database systems relies on matching select-conditions with attribute values. Thus, different mechanisms were developed for database and information retrieval systems. In consequence, there is a lack of support for queries involving both retrieval and database search terms. In this work, we introduce the quantum query language (QQL). Its underlying unifying theory is based on the mathematical formalism of quantum mechanics and quantum logic. Van Rijsbergen already discussed the strong relation between the formalism of quantum mechanics and information retrieval. In this work, we interrelate concepts from database query processing to concepts from quantum mechanics and logic. As result, we obtain a common theory which allows us to incorporate seamlessly retrieval search into traditional database query processing.     

Atlas: a nested relational database system for text applications

Advanced database applications require facilities such as text indexing, image storage, and the ability to store data with a complex structure. However, these facilities are not usually included in traditional database systems. In this paper we describe Atlas, a nested relational database system that has been designed for text-based applications. The Atlas query language is TQL, an SQL-like query language with text operators. The query language is supported by signature file text indexing techniques, and by a parser that can be configured for different text formats and even some foreign languages. Atlas can also be used to store images and audio     

Ontologies are not the Panacea in Data Integration: A Flexible Coordinator to Mediate Context Construction

Shared ontologies describe concepts and relationships to resolve semantic conflicts amongst users accessing multiple autonomous and heterogeneous information sources. We contend that while ontologies are useful in semantic reconciliation, they do not guarantee correct classification of semantic conflicts, nor do they provide the capability to handle evolving semantics or a mechanism to support a dynamic reconciliation process. Their limitations are illustrated through a conceptual analysis of several prominent examples used in heterogeneous database systems and in natural language processing. We view semantic reconciliation as a nonmonotonic query-dependent process that requires flexible interpretation of query context, and as a mechanism to coordinate knowledge elicitation while constructing the query context. We propose a system that is based on these characteristics, namely the SCOPES (Semantic Coordinator Over Parallel Exploration Spaces) system. SCOPES takes advantage of ontologies to constrain exploration of a remote database during the incremental discovery and refinement of the context within which a query can be answered. It uses an Assumption-based Truth Maintenance System (ATMS) to manage the multiple plausible contexts which coexist while the semantic reconciliation process is unfolding, and the Dempster-Shafer (DS) theory of belief to model the likelihood of these plausible contexts.     

Cooperative Query Answering with Generalized Quantifiers

The use of Generalized Quantifiers in query languages was introduced independently in (Hsu and Parker, 1995; Gyssens et al., 1995). In both cases it is argued that GQs make query languages more able to handle complex queries in a declarative way and provide a syntax more similar to natural language. In this paper we argue that query languages with Generalized Quantifiers can be used to produce cooperative question answering (Gaasterland et al., 1992). We introduce the Query Language with Generalized Quantifiers QLGQ and review related work in cooperative query answering, focusing on research that has direct connections with the results of this paper. Then we show how to use Generalized Quantifiers in dealing with false presuppositions, constructing justifications, and query relaxation. For each technique, we give examples that suggest that Generalized Quantifiers are better suited to the application of the technique than traditional approaches.     

PICASSO: A graphical query language

PICASSO (PICture Aided Sophisticated Sketch Of database queries) is a graphics-based database query language designed for use with a universal relation database system. The primary objective of PICASSO is ease of use. Graphics are used to provide a simple method of expressing queries and to provide visual feedback to the user about the system's interpretation of the query. Inexperienced users can use the graphical feedback to aid them in formulating queries whereas experienced users can ignore the feedback. Inexperienced users can pose queries without knowing the details of underlying database schema and without learning the formal syntax of SQL-like query language. This paper presents the syntax of PICASSO queries and compares PICASSO queries with similar queries in standard relational query languages. Comparisons are also made with System/U, a non-graphical universal relation system on which PICASSO is based. The hypergraph semantics of the universal relation are used as the foundation for PICASSO and their integration with a graphical workstation enhances the usability of database systems.     

基于E-R图的关系数据库关键字查询

随着信息检索技术和数据库理论的发展,如何通过信息检索技术在关系数据库中获取有用信息,并使普通用户也可以完成在关系数据库中的关键字查询,成为近期研究人员研究的热点.基于关键字的关系数据库查询系统无需用户了解数据库模式和结构化查询语言,用户只需输入几个关键字就可以得到查询结果.基于关系数据库的原型E-R图,根据意义的不同对实体进行分组.查询时根据关键字所属关系表,确定查询的实体集合,划定查询范围,提高查询效率.提出了新的算法来提高系统的查准率.最后,通过实验对E-RKS系统效能进行验证.