Carlos A. Hurtado

Query recommendation using query logs in search engines

In this paper we propose a method that, given a query submitted to a search engine, suggests a list of related queries The related queries are based in previously issued queries, and can be issued by the user to the search engine to tune or redirect the search process The method proposed is based on a query clustering process in which groups of semantically similar queries are identified The clustering process uses the content of historical preferences of users registered in the query log of the search engine The method not only discovers the related queries, but also ranks them according to a relevance criterion Finally, we show with experiments over the query log of a search engine the effectiveness of the method.

Introducing Time into RDF

The resource description framework (RDF) is a metadata model and language recommended by the W3C. This paper presents a framework to incorporate temporal reasoning into RDF, yielding temporal RDF graphs. We present a semantics for these kinds of graphs which includes the notion of temporal entailment and a syntax to incorporate this framework into standard RDF graphs, using the RDF vocabulary plus temporal labels. We give a characterization of temporal entailment in terms of RDF entailment and show that the former does not yield extra asymptotic complexity with respect to nontemporal RDF graphs. We also discuss temporal RDF graphs with anonymous timestamps, providing a theoretical framework for the study of temporal anonymity. Finally, we sketch a temporal query language for RDF, along with complexity results for query evaluation that show that the time dimension preserves the tractability of answers

Foundations of semantic web databases

The Semantic Web is based on the idea of adding more machine-readable semantics to web information via annotations written in a language called the Resource Description Framework (RDF). RDF resembles a subset of binary first-order logic including the ability to refer to anonymous objects. Its extended version, RDFS, supports reification, typing and inheritance. These features introduce new challenges into the formal study of sets of RDF/RDFS statements and languages for querying them. Although several such query languages have been proposed, there has been little work on foundational aspects. We investigate these, including computational aspects of testing entailment and redundancy. We propose a query language with well-defined semantics and study the complexity of query processing, query containment, and simplification of answers.

Temporal RDF

The Resource Description Framework (RDF) is a metadata model and language recommended by the W3C. This paper presents a framework to incorporate temporal reasoning into RDF, yielding temporal RDF graphs. We present a semantics for temporal RDF graphs, a syntax to incorporate temporality into standard RDF graphs, an inference system for temporal RDF graphs, complexity bounds showing that entailment in temporal RDF graphs does not yield extra asymptotic complexity with respect to standard RDF graphs and sketch a temporal query language for RDF.

Updating OLAP dimensions

OLAP systems support data analysis through a multidimensional data model, according to which data facts are viewed as points in a space of application-related “dimensions” , organized into levels which conform a hierarchy. Although the usual assumption is that these points reflect the dynamic aspect of the data warehouse while dimensions are relatively static, in practice it turns out that dimension updates are often necessary to adapt the multidimensional database to changing requirements. These updates can take place either at the structural level (e.g. addition of categories or modification of the hierarchical structure) or at the instance level (elements can be inserted, deleted, merged, etc.). They are poorly supported (or not supported at all) in current commercial systems and have not been addressed in the literature. In a previous paper we introduced a formal model supporting dimension updates. Here, we extend the model, adding a set of semantically meaningful operators which encapsulate common sequences of primitive dimension updates in a more efficient way. We also formally define two mappings (normalized and denormalized) from the multidimensional to the relational model, and compare an implementation of dimension updates using these two approaches.

Modeling user search behavior

Web usage mining is a main research area in Web mining focused on learning about Web users and their interactions with Web sites. Main challenges in Web usage mining are the application of data mining techniques to Web data in an efficient way and the discovery of non trivial user behaviour patterns. In this paper we focus the attention on search engines analyzing query log data and showing several models about how users search and how users use search engine results.

Capturing summarizability with integrity constraints in OLAP

In multidimensional data models intended for online analytic processing (OLAP), data are viewed as points in a multidimensional space. Each dimension has structure, described by a directed graph of categories, a set of members for each category, and a child/parent relation between members. An important application of this structure is to use it to infer summarizability, that is, whether an aggregate view defined for some category can be correctly derived from a set of precomputed views defined for other categories. A dimension is called structurally heterogeneous if two members in a given category are allowed to have ancestors in different categories. In this article, we propose a class of integrity constraints, dimension constraints, that allow us to reason about summarizability in heterogeneous dimensions. We introduce the notion of frozen dimensions which are minimal homogeneous dimension instances representing the different structures that are implicitly combined in a heterogeneous dimension. Frozen dimensions provide the basis for efficiently testing the implication of dimension constraints and are a useful aid to understanding heterogeneous dimensions. We give a sound and complete algorithm for solving the implication of dimension constraints that uses heuristics based on the structure of the dimension and the constraints to speed up its execution. We study the intrinsic complexity of the implication problem and the running time of our algorithm.

Foundations of Semantic Web databases

The Semantic Web is based on the idea of a common and minimal language to enable large quantities of existing data to be analyzed and processed. This triggers the need to develop the database foundations of this basic language, which is the Resource Description Framework (RDF). This paper addresses this challenge by: 1) developing an abstract model and query language suitable to formalize and prove properties about the RDF data and query language; 2) studying the RDF data model, minimal and maximal representations, as well as normal forms; 3) studying systematically the complexity of entailment in the model, and proving complexity bounds for the main problems; 4) studying the notions of query answering and containment arising in the RDF data model; and 5) proving complexity bounds for query answering and query containment.

OLAP dimension constraints

In multidimensional data models intended for online analytic processing (OLAP), data are viewed as points in a multidimensional space. Each dimension has structure, described by a directed graph of categories, a set of members for each category, and a child/parent relation between members. An important application of this structure is to use it to infer summarizability, that is, whether an aggregate view defined for some category can be correctly derived from a set of precomputed views defined for other categories. A dimension is called heterogeneous if two members in a given category are allowed to have ancestors in different categories. In previous work, we studied the problem of inferring summarizability in a particular class of heterogeneous dimensions. In this paper, we propose a class of integrity constraints and schemas that allow us to reason about summarizability in general heterogeneous dimensions. We introduce the notion of frozen dimensions, which are minimal homogeneous dimension instances representing the different structures that are implicitly combined in a heterogeneous dimension. Frozen dimensions provide the basis for efficiently testing implication of dimension constraints, and are useful aid to understanding heterogeneous dimensions. We give a sound and complete algorithm for solving the implication of dimension constraints, that uses heuristics based on the structure of the dimension and the constraints to speed up its execution. We study the intrinsic complexity of the implication problem, and the running time of our algorithm.

Expressive languages for path queries over graph-structured data

For many problems arising in the setting of graph querying (such as finding semantic associations in RDF graphs, exact and approximate pattern matching, sequence alignment, etc.), the power of standard languages such as the widely studied conjunctive regular path queries (CRPQs) is insufficient in at least two ways. First, they cannot output paths and second, more crucially, they cannot express relations among paths. We thus propose a class of extended CRPQs, called ECRPQs, which add regular relations on tuples of paths, and allow path variables in the heads of queries. We provide several examples of their usefulness in querying graph structured data, and study their properties. We analyze query evaluation and representation of tuples of paths in the output by means of automata. We present a detailed analysis of data and combined complexity of queries, and consider restrictions that lower the complexity of ECRPQs to that of relational conjunctive queries. We study the containment problem, and look at further extensions with first-order features, and with non-regular relations that express arithmetic properties of paths, based on the lengths and numbers of occurrences of labels.