The Browser-Based GLAUx Treebank Infrastructure: Framework, Functionality, and Future

The development of complex and consistent linguistic annotations over large and varied corpora requires an approach which allows for the incremental improvement of existing annotations by encoding all manual effort in such a way that its value is preserved and enhanced even as the resource is improved over time. This manual effort includes both annotation design and disambiguation; in the case of syntactico-semantic annotations, the former can be encoded in a machine-readable grammar and the latter as a series of decisions made at a level of granularity which supports both efficient human disambiguation and later machine re-use of the individual decisions. The general approach can be applied beyond syntactico-semantic annotation to any annotation project where the design of the representations can be encoded as a grammar, and thus we frame our methodological discussion in terms of incremental improvement, with syntactico-semantic annotations as a case study.

The Colorado Richly Annotated Full Text (CRAFT) corpus consists of full-text journal articles. The primary motivation for the annotation project was the accumulating body of evidence indicating that the bodies of journal articles contain much information that is not present in the abstracts, and that the textual and structural characteristics of article bodies are different from those of abstracts. The development of CRAFT was characterized by a “multi-model” annotation task. The sample population was all journal articles that had been used by the Mouse Genome Informatics group as evidence for at least one Gene Ontology or Mouse Phenotype Ontology “annotation.” The linguistic annotation is represented in the widely known Penn Treebank format (Marcus et al., Comput. Linguist. 19(2), 313–330, 1993) [50], with the addition of a small number of tags and phrasal categories to accommodate the idiosyncrasies of the domain.

Web search engines often federate many user queries to relevant structured databases. For example, a product related query might be federated to a product database containing their descriptions and specifications. The relevant structured data items are then returned to the user along with web search results. However, each structured database is searched in isolation. Hence, the search often produces empty or incomplete results as the database may not contain the required information to answer the query. In this paper, we propose a novel integrated search architecture. We establish and exploit the relationships between web search results and the items in structured databases to identify the relevant structured data items for a much wider range of queries.Our architecture leverages existing search engine components to implement this functionality at very low overhead. We demonstrate the quality and efficiency of our techniques through an extensive experimental study.

A relational database of protein structure has been developed to enable rapid and flexible enquiries about the occurrence of many aspects of protein architecture. The coordinates of 294 proteins from the Brookhaven Data Bank have been processed by standard computer programs to generate many additional terms that quantify aspects of protein structure. These terms include solvent accessibility, main-chain and side-chain dihedral angles, and secondary structure. In a relational database, the information is stored in tables with columns holding the different terms and rows holding the different entries for the terms. The different relational base tables store the information about the protein coordinate set, the different chains in the protein, the amino acid residues and ligands, the atomic coordinates, the salt bridges, the hydrogen bonds, the disulphide bridges and the close tertiary contacts. The database was established under ORACLE management system. Enquiries are constructed in ORACLE using SQL (structured query language) which is simple to use and alleviates the need for extensive computer programs. A single table can be searched for entries that meet various criteria, e.g. all protein solved to better than a given resolution. The power of the database occurs when several tables, or the entries in a single table, are cross-correlated. For example the dihedral angles of proline in the fourth position in an alpha-helix in high resolution structures can be rapidly obtained. The structural database provides a powerful tool to obtain empirical rules about protein conformation. This database of protein structures is part of a joint project between Birkbeck College and Leeds University to establish an integrated data resource of protein sequences and structures (ISIS) that encodes the complex patterns of residues and coordinates that define protein conformation. The entire data resource (ISIS) will provide a system to guide all areas of protein modelling including structure prediction, site-directed mutagenesis and de novo protein design. The availability of ISIS is described in the paper.

The needs of engineers in their interaction with engineering data bases are very different from those of their counter-parts in the business world. Business data base management system interfaces typically provide only a single mode of textual communication, usually a structured query language. However, in an idealengineering data base interface, an engineer would be able to define constraints, give examples, point at parts of pictures, and (sometimes) use several modes of communication simultaneously. The paper presents an example from an engineering design application to show how a traditional query language can be enhanced to accommodate the engineering needs. The paper further describes a conceptual approach for multimodal engineering data base interface combining multipurpose graphics, an engineering query language, and other interface methodologies in an engineering workstation environment.

The DBMS applications are becoming increasingly popular in the scientific community to support the interactive exploration of huge data. A result of heavy usage has also lead to a lot of tavles generated in the warehouse. This has tremendously increased the need for recommendation system & various tools for the user as user is not capable to explore such huge data by using Structured Query language. This motivates to turn towards the idea of query recommendation system which will assist the technical & non-technical users to generate top-N query recommendations as per their needs. In this survey paper, the focus is given on opportunities that exist in domain of query recommendation, brief description of recommendation outline and techniques. Along with this, the terminology to identify the similarity and comparison of fragment based approach & matrix factorization approach is also explored. The Database Management Systems are used to organize, maintain and retrieve the huge amount of data. To acquire the essential data the user need to interact with the database by taking the support of declarative Structured Query Language (SQL). Most of times, it is observed that user faces the difficulties in interacting with the database by using SQL query language as the database have hundreds of schema's and thousands of attributes. This problem has been solved with the support of Database Management Applications such as SAP, Easy Query, and Microsoft Access. These applications involve the user interaction and manual editing of the SQL query components but when the user is unacquainted about the underlying database structure then it becomes difficult for the user to formulate the query. To formulate the query, the research work has been done (1) and that results into the query assistant tool which helps the user to either formulate the query or to recommend the relevant query items based on formulated query. This work is the reflection of the web recommendation techniques those are used in gaining the on-line marketing intelligence. The web recommendation techniques and algorithms have their strong relation with the Information Retrieval Science (IR). In IR, the recommendation techniques and algorithms are used to retrieve the most relevant top K documents as per the formulated query. Most of times the Business Verticals have their own off-line database and the user will be interested in exploration of the database and faces the difficulties. Therefore, it may also possible to extend the idea specified by the authors (1) to provide the Query Recommendation Assistant Tool that enable the user to formulate and refine the SQL query. This take off to cataloged view on how to make the imperative use of IR and the web recommendation techniques to generate and recommend the top K relevant query objects by identifying the similarities among the SQL query fragments. This becomes the novel approach that handles crucial responsibility in proposing the assistant tool to retrieve data over the database. The rest of the paper is organized as follows: section-2 describes the related work and the section-3 concentrates on recommendation outline. The section-4 describes the recommendation techniques and similarity metrics those have been used in finding the similarity among the query fragments. The section-5 focuses on terminology used to calculate weights of items required for finding similarity. The section-6 states the comparison between the fragment based approach and matrix factorization approach.

Bioinformatics is a scientific field on the border between informatics and biology where problems in the field of biology are solved using statistical methods. Another part of it are database systems which serve to store data necessary for meta-analysis. In recent years, there has been a boom mainly thanks to enabling technologies that make it possible to obtain big data about the functioning of living cells of organisms. Bioinformatics tools are necessary to process these data and form an integral part of research in modern biological and medical sciences. Scientific research focused on molecular biology, as well as medicine, is increasingly focusing on data storage. It is understood that the correct structure of the database is important for the correct interpretation of the results of their research activities. For communication between tables in the database, it is essential to set the data type, assign Primary key and Foreign key, ensure data integrity, remove data plurality and understand the research logic. Based on these needs, we created a relational database using SQL Server 2017 and Microsoft SQL Server Management Studio 2017 (SSMS). We created the source code for programming the database and filling it with data in Structured Query Language (SQL) and T-SQL on the Microsoft platform. Of the data types, we used float for numbers with a floating decimal line, integer values were assigned an integer (int), date had a date data type, and text strings had a defined nvarchar data type. Our results bring new information in the field of bioinformatics about the creation of a database structure for data storage in cell biology research. These new insights will help big data in meta-analyses of data and applying scientific results to medical and scientific practice. The database will store data obtained in real time, which will ensure relevance in pointing out biological trends, regularities, relationships and links between cellular structures. All these aspects are very important for the spatial modeling of data and the creation of models of interactions of cell structures with use for applications in medical and biological practice.

Databases have been always the most important topic in the study of information systems, and an indispensable tool in all information management systems. However, the extraction of information stored in these databases is generally carried out using queries expressed in a computer language, such as SQL (Structured Query Language). This generally has the effect of limiting the number of potential users, in particular non-expert database users who must know the database structure to write such requests. One solution to this problem is to use Natural Language Interface (NLI), to communicate with the database, which is the easiest way to get information. So, the appearance of Natural Language Interfaces for Databases (NLIDB) is becoming a real need and an ambitious goal to translate the user’s query given in Natural Language (NL) into the corresponding one in Database Query Language (DBQL). This article provides an overview of the state of the art of Natural Language Interfaces as well as their architecture. Also, it summarizes the main recent advances on the task of Natural Language Interfaces for databases.

The HITRAN2016 molecular spectroscopic database

Data security in a relational database environment

A natural language query builder interface retrieves the required data in structured form from database when query is entered in natural language. The user need not necessarily have sufficient technical knowledge of structured query language statements so nontechnical users can also use this proposed model. In natural language parsing, getting highly accurate syntactic analysis is a crucial step. Parsing of natural languages is the process of mapping an input string or a natural language sentence to its syntactic representation. Constituency parsing approach takes more time for parsing. So, natural language query builder interface is developed in which the parsing of natural language sentence is done by using dependency parsing approach. Dependency parsing technique is widespread in natural language domain because of its state-of-art accuracy and efficiency and also it performs best. In this paper, the buffering scheme is also proposed for natural language statements which will not load the whole sentence if it was done previously. Also there was a need of generalized access to all tables from database which is handled in this system.

In recent years, there has been a growing demand for the development of authentication, authorization and accounting (AAA) systems for WLAN networks. In this paper we present a network architecture of SQL database servers especially tailored for AAA functions in large WLAN systems. Proposed database network architecture is vendor independent in sense that can be deployed with different AAA server implementations. WLAN management information database for AAA purposes is center of a WLAN network management system providing control of parameters such as: authentication and authorization of users, deletion or creation of users information, storage of accounting information which can be used for billing. Detailed database structure of each SQL database server in proposed centralized-distributed AAA database network architecture is described. Working principles of network database system for WLAN AAA purposes are based on MySQL master/slave chain replication. Proposed network architecture of SQL databases offers high level of reliability, availability and scalability.