Je#rey D. Ullman. Principles of Databases and Knowledge-Base Systems, volume I. Computer Science Press, 1989.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....the search locally. That approach requires substantial programming skills and computing resources: large disk space (about 100 Giga bytes to store 12 million EST entries) a parser to parse flat files, a data normalizer to decompose parsed data into data tables that conforms the third normal form [34], and finally algorithms to identify ESTs that contain a SNP. In contrast, applying agent technologies requires much less programming skills and computing resources. Also, we can leverage available data connection established by NCBI between databases. Moreover, each execution of the agent ....

Je#rey D. Ullman. Principles of Database and Knowledge-base Systems, volume I,II. Computer Science Press, Palo Alto, CA, 1988.

....access limitation of s is that each query to s must specify a movie name. Consider the following query that asks for the awards of the movies in which Fonda starred: SELECT Award FROM r, s WHERE Star = fonda AND r.Movie = s. Movie; This query can be written as the following conjunctive query [Ull89] Q 1 : ans(A) r(fonda, M) s(M, A) To answer Q 1 , we first access relation r to retrieve the movies in which Fonda starred. For each returned movie, we access relation s to obtain its awards. Finally we return all these awards as the answer to the query. Although we did not retrieve all the ....

....in the supplementary relations [BR87] of the answerable subgoals. Thus the computability of the complete answer is data dependent. 2 Problem Formulation In this section, we formalize the problem studied in this article. We use binding patterns of relations to model their limited access patterns [Ull89] A binding pattern of a relation specifies the attributes that must be given values ( bound ) to access the relation. In each binding pattern, an attribute is adorned as b (a value must be specified for this attribute) or f (the attribute can be free) For instance, the limitation of ....

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Je#rey D. Ullman. Principles of Database and Knowledge-base Systems, Volumes II: The New Technologies. Computer Science Press, New York, 1989.

....the late 70 s and early 80 s. Database dependencies theory is still an active area of research [SF00] Her95] LL97a] LL97b] LL98] Functional and multivalued dependencies are the most known classes of data dependencies. In practice, these two kinds are sucient in general to express constraints ([Ull88]) Nevertheless, more general classes have been introduced, with the purpose of nding a uniform way to express constraints ( BV81] SU82] This paper deals with the class commonly known for generalizing most of the dependencies: that of tuple generating and equality generating dependencies (TGDs ....

Jerey D. Ullman. Principles of Database and Knowledge-Base Systems. Volume I: Classical Database Systems. Computer Science Press, 1988.

....nitons In the theory of relational algebra, a conjunctive query is a query using only Selection, Projection and Cartesian product operations. In Datalog terminology, a conjunctive query is a safe, nonrecursive rule whose predicates in the body are de ned over EDB (Extensional Database) predicates [13]. Depending on the presence or absence of built in predicates other than = in the bodies, we distinguish two types of conjunctive queries: Equality queries where built in predicates, except equality, are not allowed. The general form of an equality query is q( X) p 1 ( Y 1 ) pn ( ....

....either variables that appear in an ordinary predicate, or constants of the domain (but not both constants) and 2 f= 6= g. Queries written as Datalog rules are based on the well known concept of assignment mappings, denoting the derivation of facts as answers. An assignment mapping [13] from a query Q to a database D is a function from the symbols of Q to those of D; is the identity in the predicate names and constants, and it must map every ordinary predicate in the body of Q to a fact in D. If the query has built in predicates, the application of the assignment mapping to ....

Jerey D. Ullman. Principles of Database and Knowledge-base Systems, volume 1 and 2. Computer Science Press,

....is not a query execution plan, but rather a query referring to the view relations. 6.1 Datalog notation For this and the next section, it is necessary to revert to datalog notation and terminology. Hence, below we provide a brief reminder of datalog notation and of conjunctive queries [Ull89, AHV95] Conjunctive queries are able to express select project join queries A conjunctive query has the form: q( X) r 1 ( X 1 ) r n ( X n ) where q, and r 1 ; r n are predicate names. The predicate names r 1 ; r n refer to database relations. The atom q( ....

Jerey D. Ullman. Principles of Database and Knowledge-base Systems, Volumes I, II. Computer Science Press, Rockville MD, 1989.

....queries. We assume the reader is familiar with basic elements of SQL. As we see in Section 8, in some cases answering a query using a set of views may require that the rewriting be recursive. Hence, below we provide a brief reminder of datalog notation and of conjunctive queries [Ull89] A conjunctive query has the form: q( X) r 1 ( X 1 ) r n ( X n ) where q, and r 1 , r n are predicate names. The predicate names r 1 , r n refer to database relations. The atom q( X) is called the head of the query, and refers to the answer relation. The ....

Je#rey D. Ullman. Principles of Database and Knowledge-base Systems, Volumes I, II. Computer Science Press, Rockville MD, 1989.

....of a node being bound to the value of a string or a number, its value is bound to a table i.e. its answer formula is a table. We consider the domain of node to be a table, and the various operations on these tables may be the ones given by the relational algebra e.g. select) project) etc. [Ull88]. We may also include some optional predicates on tables e.g. a predicate to test whether a table includes a particular tuple. For example, table T may represent a table of students at university X. Node N may have as its answer formula the selection of students in the table in T that have a GPA ....

Jeery D. Ullman. Principles of Database and Knowledge-Base Systems, volume 1. Computer Science Press, 1988.

....the late 70 s and early 80 s. Database dependencies theory is still an active area of research [SF00] Her95] LL97a] LL97b] LL98] Functional and multivalued dependencies are the most known classes of data dependencies. In practice, these two kinds are sucient in general to express constraints ([Ull88]) Nevertheless, more general classes have been introduced, with the purpose of nding a uniform way to express constraints ( BV81] SU82] This paper deals with the class commonly known for generalizing most of the dependencies: that of tuple generating and equality generating dependencies (TGDs ....

Jerey D. Ullman. Principles of Database and Knowledge-Base Systems. Volume I: Classical Database Systems. Computer Science Press, 1988.

....and especially RDF schemas are derived from description logics. RDF is targeted as content representation for internet resources, and thus will play an important role for IR in this area. 4. 3 Datalog Datalog is a logic programming language that has been developed in the database field (see e.g. [20], 2] Like Prolog, it is based on horn logic. However, in contrast to Prolog, it does not allow for functions as terms, and the use of negation is restricted. Due to these constraints, there are sound and complete evaluation algorithms for Datalog in contrast to Prolog, where certain ....

Je#rey D. Ullman. Principles of Database and Knowledge-Base Systems,volumeI. Computer Science Press, Rockville (Md.), 1988.

....[94] We show that the complexity of computation is directly related to the size of the labels in the intersection graph. 4.1 A Partition Based SAT Procedure The algorithm we propose uses a SAT procedure as a subroutine and is backtrack free. We describe the algorithm using database notation [111]. # p 1 , p k T is the projection operation on a relation T . It produces a relation that includes all the rows of T , but only the columns named p 1 , p k (suppressing duplicate rows) S 1 R is the natural join operation on the relations S and R. It produces the cross product of S, R, ....

Je#rey D. Ullman. Principles of Database and knowledge-base systems, volume 1. Computer Science Press, 1988.

....Table INRIA A Performance Evaluation of Alternative Mapping Schemes for Storing XML Data in a Relational Database11 3.1.3 Universal Table The third approach we study generates a single Universal table to store all the attributes of an XML document. This corresponds to a Universal table [34] with separate columns for all the attribute names that occur in the XML document. Conceptionally, this Universal table corresponds to the result of an outer join of all Attribute tables. The structure of the Universal table is as follows, if n 1 ; n k are the attribute names in the XML ....

Jerey D. Ullman. Principles of Database and Knowledge-base Systems, Volumes I, II. Computer Science Press, Rockville MD, 1989.

....(4) Individual concept quantification is obviously essential here. ##)##x, y.#[x =#c # y =##]#(#c, ##) 4) 5 Databases With a Single Relation In this section we begin taking a look at relational databases. What we consider is quite basic, and can be found in any textbook on databases [4] is a good source. Relational databases are commonly reasoned about using classical firstorder logic. I want to show that modal logic is also a natural tool for this purpose. For now, only a single relation will be considered this will be extended later. Modality and Databases 7 The record is ....

Je#rey D. Ullman. Principles of Database and Knowledge-Base Systems, volume 1.

....access to Web documents. Its usage is described in Section 13. Florid 2.1 and 2.2 (1999) contain several internal modi cations that improve on speed and usability. We assume that the reader of this tutorial is familiar with the basic concepts of deductive databases, e.g. Datalog [AHV95, CGT90, Ull89] and the principles of object oriented database systems [ABD 89] We refer the reader to the user manual [MM99] for a description of Florid system commands. Please send enquiries, comments, suggestions, and bug reports to florid informatik.uni.freiburg.de 2 A First Example Before ....

....are not removed from the object base. So John is an adulterer because he kissed his wife. Note: This behavior is due to the pure in ationary treatment of negation and only avoidable by strati cation. However, this program is not strati ed because the corresponding dependency graph is cyclic [Ull89] Another solution of this problem is be the application of the well founded semantics [VGRS91] See Example 14.10. 14.9 Speed up Inheritance tones.flp Calculates the intervals between tones within one octave Heavy use of inheritance triggering 14 SOME EXAMPLE PROGRAMS 46 base ....

Jerey D. Ullman. Principles of Database and Knowledge-Base Systems, volume 2. Computer Science Press, New York, 1989.

....driven schema de nition, multiple, non monotonic inheritance and furthermore path expressions [FLU94] that can also be used for anonymous object creation. The evaluation of programs is based on a set oriented bottom up computation extension of the algorithm well known from Datalog [AHV95, CGT90, Ull89] also a semi naive evaluation component is provided. With version 2.0, Florid has been extended with Web access (see tutorial [FHM 99] for details) The Florid system was developed at the universities of Mannheim and Freiburg as part of a research project granted by the DFG (Deutsche ....

Jerey D. Ullman. Principles of Database and Knowledge-Base Systems, volume 2. Computer Science Press, New York, 1989.

....set is an EMS of V . As shown in Example 4.1, a view set can have multiple EMS s. In some scenarios we need to answer queries using views in the presence of constraints (e.g. functional dependencies [Cod70] multivalued dependencies [Fag77, Del78] and binding limitations on views [RSU95, DL97, Ull89, LC00, LYV 98, YLUGM99] We can generalize our results by requiring that the algorithm Check F take constraints and binding limitations into consideration. RSU95, Gry99] give algorithms for answering conjunctive queries using conjunctive views in these scenarios; Dus97] provides answers ....

Jerey D. Ullman. Principles of Database and Knowledge-base Systems, Volumes II: The New Technologies. Computer Science Press, New York, 1989.

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Je#rey D. Ullman. Principles of Databases and Knowledge-Base Systems, volume I. Computer Science Press, 1989.

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D. Je#rey Ullman. Principles of Database and Knowledge-Base Systems, volume 2. Computer Science Press, 1989.

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Jerey D. Ullman. Principles of Database and Knowledge-base Systems, Volumes I, II. Computer Science Press, Rockville MD, 1989.

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Jerey D. Ullman. Principle of database and knowledge-base systems,volume I of Principle of computer science series. Computer Science Press, Inc., 1988.

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Jerey D. Ullman. Principle of database and knowledge-base systems. Principle of computer science series. Computer Science Press, Inc., 1988.

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Jerey D. Ullman. Principles of Database and Knowledge-base Systems, Volumes I, II. Computer Science Press, Rockville MD, 1989.

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Jerey D. Ullman. Principle of database and knowledge-base systems,volume I of Principle of computer science series. Computer Science Press, Inc., 1988.

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Jerey D. Ullman. Principles of Database and Knowledge-Base Systems. Computer Science Press, Rockville, Md., 1988.

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Je#rey D. Ullman. Principles of Database and Knowledge-Base Systems, Volume 2. Computer Science Press, 1989.

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Je#rey D. Ullman. Principles of Database and Knowledge Base Systems,volume 1. Computer Science Press, Potomac, Maryland, 1988.

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