Candidate Keys Research Articles

On concise set of relative candidate keys

Matching keys, specifying what attributes to compare and how to compare them for identifying the same real-world entities, are found to be useful in applications like record matching, blocking and windowing [7]. Owing to the complex redundant semantics among matching keys, capturing a proper set of matching keys is highly non-trivial. Analogous to minimal/candidate keys w.r.t. functional dependencies, relative candidate keys (RCKs [7], with a minimal number of compared attributes, see a more formal definition in Section 2) can clear up redundant semantics w.r.t. "what attributes to compare". However, we note that redundancy issues may still exist among rcks on the same attributes about "how to compare them". In this paper, we propose to find a concise set of matching keys, which has less redundancy and can still meet the requirements on coverage and validity. Specifically, we study approximation algorithms to efficiently discover a near optimal set. To ensure the quality of matching keys, the returned results are guaranteed to be RCKs (minimal on compared attributes), and most importantly, minimal w.r.t. distance restrictions (i.e., redundancy free w.r.t. "how to compare the attributes"). The experimental evaluation demonstrates that our concise RCK set is more effective than the existing rck choosing method. Moreover, the proposed pruning methods show up to 2 orders of magnitude improvement w.r.t. time costs on concise RCK set discovery.

SWITCHING-ALGEBRAIC ANALYSIS OF RELATIONAL DATABASES

There is an established equivalence between relational database Functional Dependencies (FDs) and a fragment of switching algebra that is built typically of Horn clauses. This equivalence pertains to both concepts and procedures of the FD relational database domain and the switching algebraic domain. This study is an exposition of the use of switching-algebraic tools in solving problems typically encountered in the analysis and design of relational databases. The switching-algebraic tools utilized include purely-algebraic techniques, purely-visual techniques employing the Karnaugh map and intermediary techniques employing the variable-entered Karnaugh map. The problems handled include; (a) the derivation of the closure of a Dependency Set (DS), (b) the derivation of the closure of a set of attributes, (c) the determination of all candidate keys and (d) the derivation of irredundant dependency sets equivalent to a given DS and consequently the determination of the minimal cover of such a set. A relatively large example illustrates the switching-algebraic approach and demonstrates its pedagogical and computational merits over the traditional approach.

Map Derivation of the Closures for Dependency and Attribute Sets and all Candidate Keys for a Relational Database

Map Derivation of the Closures for Dependency and Attribute Sets and all Candidate Keys for a Relational Database

An Optimization of Association Rule Mining using K-Map and Genetic Algorithm for Large Database

Rule mining is very efficient technique for find relation of correlated data. The correlation of data gives meaning full extraction process. For the mining of rule mining a variety of algorithm are used such as Apriori algorithm and tree based algorithm. Some algorithm is wonder performance but generate negative association rule and also suffered from multi-scan problem. In this paper we proposed a k-apriori-GA association rule mining based on genetic algorithm and K-map formula. In this method we used a k-map binary table for partition of data table as 0 and 1. The divided process reduces the scanning time of database. The proposed algorithm is a combination of kpartition and near distance of k-map candidate key. Support weight key is a vector value given by the transaction data set. The process of rule optimization we used genetic algorithm and for evaluate algorithm conducted the real world dataset The National Rural Employment Guarantee Act (NREGA) Department of Rural Development Government of India.

Text sentiment analysis-oriented commodity review detection

To help sellers timely and effectively get the commodity reviews,the author proposed a commodity review detection method based on the key word extraction.Based on the Chinese word segmentation,this method firstly extracted the candidate Key words based on part of speech tagging,and then filtered out noises based on the rules.The paper extracted the dynamic co-occurrence of the commodity reviews,and extended the Key words based on these dynamic co-occurrences.Finally the commodity review detection method based on the keyword was realized.The experimental results show that,compared to the basic model,the proposed method can increase the F-Measure by 34.8%,which proves that efficient key word extraction is very useful to the commodity review detection.

Algorithm for Relational Database Normalization Up to 3NF

When an attempt is made to modify tables that have not been sufficiently normalized undesirable sideeffects may follow. This can be further specified as an update, insertion or deletion anomaly depending on whether the action that causes the error is a row update, insertion or deletion respectively. If a relation R has more than one key, each key is referred to as a candidate key of R. Most of the practical recent works on database normalization use a restricted definition of normal forms where only the primary key (an arbitrary chosen key) is taken into account and ignoring the rest of candidate keys. In this paper, we propose an algorithmic approach for database normalization up to third normal form by taking into account all candidate keys, including the primary key. The effectiveness of the proposed approach is evaluated on many real world examples.

An Efficient Methodology for the Evaluations of Select Operation in Query Optimization

brought the mutiny in the Information technology by making users free from the burden of developing logic for solution of the application problem. At the same time, it enhanced the need for implementation of ameliorated strategies to evaluate the intermediate operations. The development of 4GLs freed the users from the strained design of ‘how to do it’ for solutions of their applications. At the back end, it increased the complexity of transformation from non-procedural query to procedural query. The query processing and optimization manages these transformations, by transforming 4GLs query into appropriate relational algebra/calculus expression in the first phase, minimizing the operations in the next phase and then evaluating the expression through the efficient strategies for such operations in the third phase. The transformation to relational algebra/calculus expression and minimizing operations are straightforward processes. The development of ameliorated strategies depends on the file organizations used in the storing relations of the database (Secondary storage structures). This paper discusses the strategies designed for select operation, when tuples of operand relations are stored in one of various file organizations in the database. Here, an attempt is made to design ameliorated algorithms to evaluate select operation when the tuples of the operand relations are stored in any of the file organizations like (i) sequential file (ii) indexed sequential files with B-tree file having number of key field indexes in each node and B+ tree file organizations for multiple indexes where data pointers are stored in each leaf node of the multilevel indexes of the file organization. The literature available suggests that, there are good methods available when key fields are primary keys. The authors have not noticed any clear cut strategies, when key fields for indexing are non primary keys (non candidate keys). Here, an attempt is made to develop the strategies, when key fields are non-candidate keys.

An evolutionary computation attack on one-round TEA

In this work, one-round Tiny Encryption Algorithm (TEA) is attacked with an Evolutionary Computation method inspired by a combination of Genetic Algorithm (GA) and Harmony Search (HS). The system presented evaluates and evolves a population of candidate keys and compares paintext-ciphertext pairs of the known key against said population. We verify that randomly generated keys are the hardest to derive. Keys composed of words containing all on-bits are more difficult to break than keys composed of words containing all off-bits. Keys which have repeated words are easiest to derive. Finally, the present EC strategy is capable of deriving degenerate keys; this is most evident when keys are front loaded so that the first byte of each word has the highest density of on-bits.

Dynamic constraints for record matching

This paper investigates constraints for matching records from unreliable data sources. (a) We introduce a class of matching dependencies (mds) for specifying the semantics of unreliable data. As opposed to static constraints for schema design, mds are developed for record matching, and are defined in terms of similarity predicates and a dynamic semantics. (b) We identify a special case of mds, referred to as relative candidate keys (rcks), to determine what attributes to compare and how to compare them when matching records across possibly different relations. (c) We propose a mechanism for inferring mds, a departure from traditional implication analysis, such that when we cannot match records by comparing attributes that contain errors, we may still find matches by using other, more reliable attributes. Moreover, we develop a sound and complete system for inferring mds. (d) We provide a quadratic-time algorithm for inferring mds and an effective algorithm for deducing a set of high-quality rcks from mds. (e) We experimentally verify that the algorithms help matching tools efficiently identify keys at compile time for matching, blocking or windowing and in addition, that the md-based techniques effectively improve the quality and efficiency of various record matching methods.

Understanding User Behavior using Web Usage Mining

usage mining is about analyzing the user interactions with a web server based on resources like web logs, click streams and database transactions. It helps in discovering the browsing patterns of the user and in relating the pages visited by him. This knowledge can be of help in making business decisions, refining the web site design to derive personalized pages. Web usage mining uses the data mining and the incremental mining techniques to extract the user usage patterns and study the visiting characteristics of the user. Normally, the source for all this data is the web server log, which changes dynamically. Conventional data mining techniques were proposed to be inefficient, as they need to be re-executed every time the log changes which in turn requires multiple database scans. This paper discusses an algorithm to suit the dynamically changing log scenario, based on association rule mining with incremental technique. The algorithm proved to be more efficient as there are redundant no of scans of database; it avoids the generation of candidate keys and allows interactive mining with different supports. The experimental results proving this claim are given in this paper.

Reasoning about record matching rules

To accurately match records it is often necessary to utilize the semantics of the data. Functional dependencies (FDs) have proven useful in identifying tuples in a clean relation, based on the semantics of the data. For all the reasons that FDs and their inference are needed, it is also important to develop dependencies and their reasoning techniques for matching tuples from unreliable data sources. This paper investigates dependencies and their reasoning for record matching. (a) We introduce a class of matching dependencies (MDs) for specifying the semantics of data in unreliable relations, defined in terms of similarity metrics and a dynamic semantics . (b) We identify a special case of MDs, referred to as relative candidate keys (RCKs), to determine what attributes to compare and how to compare them when matching records across possibly different relations. (c) We propose a mechanism for inferring MDs, a departure from traditional implication analysis, such that when we cannot match records by comparing attributes that contain errors, we may still find matches by using other, more reliable attributes. (d) We provide an O ( n 2 ) time algorithm for inferring MDs, and an effective algorithm for deducing a set of RCKs from MDs. (e) We experimentally verify that the algorithms help matching tools efficiently identify keys at compile time for matching, blocking or windowing, and that the techniques effectively improve both the quality and efficiency of various record matching methods.

An efficient algorithm for 3NF determination

In this paper we present an algorithm that determines whether or not a relation R is in Third Normal Form (3NF). The algorithm works by classifying the attributes of R into so-called dependency sets that are based on the set of functional dependencies defined on R. A new type of dependency graph is introduced to visualize the dependencies. The algorithm will run faster than algorithms designed to find all of the candidate keys of R, especially if there exists more than one dependency set.

Extracting the extended entity-relationship model from a legacy relational database

The maintenance of an existing database depends on the depth of understanding of its characteristics. Such an understanding is easily lost when the developers disperse. The situation becomes worse when the related documentation is missing. This paper addresses this issue by extracting the extended entity-relationship schema from the relational schema. We developed algorithms that investigate characteristics of an existing legacy database in order to identify candidate keys of all relations in the relational schema, to locate foreign keys, and to decide on the appropriate links between the given relations. Based on this analysis, a graph consistent with the entity-relationship diagram is derived to contain all possible uniary and binary relationships between the given relations. The minimum and maximum cardinalities of each link in the mentioned graph are determined, and extra links within the graph are identified and categorized, if any. The latter information is necessary to optimize foreign keys related information. Finally, the last steps in the process involve~(when applicable) suggesting improvements on the original conceptual design, deciding on relationships with attributes, many-to-many and n-ary ( n⩾3) relationships, and identifying is-a links. User involvement in the process is minimized to the case of having multiple choices, where the system does not have the semantic knowledge required to decide on a certain choice.

Normalization of Relations with Nulls in Candidate Keys

This paper discusses normalization of relations when the candidate keys of a relation have missing information represented by nulls. The paper shows that when the missing information is of the type “not applicable” or “does not exist,” problems and confusion can arise in normalizing relations. Candidate keys with missing information commonly are found in relations that represent information on two entities with a one-to-one relationship between them. The current definition of Boyce-Codd Normal Form (BCNF) is ineffective in identifying poor designs in such relations that may have insertion/deletion anomalies. It is shown that the above problem can be corrected by incorporating the concept of entity integrity rule into the definition of BCNF. This paper also shows that incorporating the entity integrity rule into the definition of either a relation or a candidate key does not provide a satisfactory solution to the problem.

From ternary relationship to relational tables

The transformation from n-ary relationships to a relational database schema has never been really fully analyzed. This paper presents one of the several ternary cases ignored by the ER-to-RM literature. The case shows that the following common belief is wrong: Given a set of FDs over a table resulting in a non-3NF situation, it is always possible to obtain a fully equivalent set of 3NF tables, without adding other restrictions than candidate keys and elementary inclusion dependencies.

A pedagogical approach to database design via Karnaugh maps

The study of normalization is a fundamental topic that is covered in most introductory database courses taught by departments of Computer/Electrical Engineering and Computer Science. The typical pedagogical approach to normalization presents several classical algorithms, which are based upon the application of axioms and lemmas for manipulating functional dependencies, that can be used in the process of relational decomposition and synthesis. In this paper, an augmentation to the traditional pedagogical strategy is presented for introducing students to normalization and relational synthesis concepts. This augmentation transforms semantic concepts into Boolean form that can be easily manipulated with the Karnaugh map. The Karnaugh map provides an especially useful method for illustrating the process of determining the candidate keys of a relation, as well as simplifying the mechanics of manipulating functional dependencies that are required for database decomposition and synthesis. Moreover, students find the Karnaugh-map-based techniques faster for most calculations, as well as easier to apply than conventional algorithms, since most engineering students are more familiar with combinatorial Boolean algebra than the algebra of functional relations.

An Efficient Algorithm to Compute the Candidate Keys of a Relational Database Schema

We provide an efficient algorithm for computing the candidate keys of a relational database schema. The algorithm exploits the 'arrangement' of attributes in the functional dependencies to determine which attributes are essential and useful for determining the keys and which attributes should not be considered. A more generalized algorithm using attribute graphs is then provided which allows a uniform and simplified solution to find all possible keys of a relational database schema when the attribute graph of Functional Dependencies (FDs) is not strongly connected.

Distributing Trust Amongst Multiple Authentication Servers12

Some recent research on key distribution systems has focussed on analysing trust in authentication servers, and constructing key distribution protocols which operate using a number of authentication servers, a minority of them may be untrusted. This paper proposes a key distribution protocol with multiple authentication servers using a cross checksum scheme. In the protocol, multiple untrusted servers generate candidate session keys for two clients. The clients use the cross checksum scheme for the verification of these candidate keys. It is not necessary for the clients to trust an individual server. A minority of corrupted and colluding servers cannot compromise security, and their inappropriate behaviour can be detected. Comparing our protocol to similar proposals, we will consider the number of messages exchanged, the length of messages, and the method of key generation.

An approach for reverse engineering of relational databases

A process for reverse engineering of relational databases is proposed. Object-oriented models provide a natural language for facilitating the re-engineering process. An object-oriented model can describe the existing software, the reverse-engineered semantic intent, and the forward-engineered new system. The Object Modeling Technique (OMT) notation for modeling data is adopted. Graphical OMT models are intuitive and provide a rigorous basis for specifying software. A more robust process than advanced in the literature is proposed. Guidelines for coping with design optimizations and unfortunate implementation decisions are provided. The process emphasizes analysis of candidate keys rather than primary keys. Three sources for information are incorporated: schema, observed patterns of data, and the semantic understanding of application intent. >

A note on relation schemes which are in 3NF but not in BCNF

We investigate the properties of relation schemes which are in third normal form (3NF) but not in Boyce-Codd normal form (BCNF) and prove that such a relation scheme must have a pair of candidate keys which overlap.