Bettina Fazzinga

Semantic Web search based on ontological conjunctive queries

Many experts predict that the next huge step forward in Web information technology will be achieved by adding semantics to Web data, and will possibly consist of (some form of) the Semantic Web. In this paper, we present a novel approach to Semantic Web search, called Serene, which allows for a semantic processing of Web search queries, and for evaluating complex Web search queries that involve reasoning over the Web. More specifically, we first add ontological structure and semantics to Web pages, which then allows for both attaching a meaning to Web search queries and Web pages, and for formulating and processing ontology-based complex Web search queries (i.e., conjunctive queries) that involve reasoning over the Web. Here, we assume the existence of an underlying ontology (in a lightweight ontology language) relative to which Web pages are annotated and Web search queries are formulated. Depending on whether we use a general or a specialized ontology, we thus obtain a general or a vertical Semantic Web search interface, respectively. That is, we are actually mapping the Web into an ontological knowledge base, which then allows for Semantic Web search relative to the underlying ontology. The latter is then realized by reduction to standard Web search on standard Web pages and logically completed ontological annotations. That is, standard Web search engines are used as the main inference motor for ontology-based Semantic Web search. We develop the formal model behind this approach and also provide an implementation in desktop search. Furthermore, we report on extensive experiments, including an implemented Semantic Web search on the Internet Movie Database.

Semantic search on the Web

Web search is a key technology of the Web, since it is the primary way to access content on the Web. Current standard Web search is essentially based on a combination of textual keyword search with an importance ranking of the documents depending on the link structure of the Web. For this reason, it has many limitations, and there are a plethora of research activities towards more intelligent forms of search on the Web, called semantic search on the Web, or also Semantic Web search. In this paper, we give a brief overview of existing such approaches, including own ones, and sketch some possible future directions of research.

Semantic web search based on ontological conjunctive queries

Many experts predict that the next huge step forward in Web information technology will be achieved by adding semantics to Web data, and will possibly consist of (some form of) the Semantic Web. In this paper, we present a novel approach to Semantic Web search, which is based on ontological conjunctive queries, and which combines standard Web search with ontological background knowledge, as it is, e.g., available in Semantic Web repositories. We show how standard Web search engines can be used as the main inference motor for processing ontology-based semantic search queries on the Web. We develop the formal model behind this approach and also provide an implementation in desktop search. Furthermore, we report on extensive experimental results.

On the Complexity of Probabilistic Abstract Argumentation Frameworks

Probabilistic abstract argumentation combines Dung’s abstract argumentation framework with probability theory in order to model uncertainty in argumentation. In this setting, we address the fundamental problem of computing the probability that a set of arguments is an <i>extension</i> according to a given semantics. We focus on the most popular semantics (i.e., <i>admissible</i>, <i>stable</i>, <i>complete</i>, <i>grounded</i>, <i>preferred</i>, <i>ideal-set</i>, <i>ideal</i>, <i>stage</i>, and <i>semistable</i>) and show the following dichotomy result: computing the probability that a set of arguments is an extension is either <i>FP</i> or <i>FP</i>^#<i>P</i>-complete depending on the semantics adopted. Our polynomial-time results are particularly interesting, as they hold for some semantics for which no polynomial-time technique was known so far.

XPath Query Relaxation through Rewriting Rules

Query relaxation is the process of weakening a query to a more general one, and it is frequently employed to support approximate query answering. In this paper, rewriting systems for a wide fragment of XPath are investigated, which accomplish query relaxation through the application of simple rewriting rules transforming navigational axes and node tests into relaxed ones. Specifically, a general yet simple form of rewriting rules is considered, which subsumes the forms adopted in several rewriting systems for approximate XPath query answering. The expressiveness of rewriting systems based on this form of rules is characterized in terms of their capability of transforming a query into every more general formulation. It is shown that traditional rewriting systems are not only incomplete w.r.t. containment, but also w.r.t. the stricter form known as containment by homomorphism. This limitation is overcome by defining a set R* of rewriting rules which are still of the same simple form of traditional ones, but are expressive enough to catch at least containment by homomorphism. Then, an algorithm is proposed which exploits R* to provide approximate answers of queries along with a measure of their approximation degree.

Efficiently Estimating the Probability of Extensions in Abstract Argumentation

Probabilistic abstract argumentation combines Dung’s abstract argumentation framework with probability theory to model uncertainty in argumentation. In this setting, we deal with the fundamental problem of computing the probability Pr sem (S) that a set S of arguments is an extension according to a semantics sem. We focus on three popular semantics (i.e., complete, grounded, and preferred) for which the state-of-the-art approach is that of estimating Pr sem (S) by using a Monte-Carlo simulation technique, as computing Pr sem (S) has been proved to be intractable. In this paper, we detect and exploit some properties of these semantics to devise a new Monte-Carlo simulation approach which is able to estimate Pr sem (S) using much fewer samples than the state-of-the-art approach, resulting in a significantly more efficient estimation technique.

Top-k Answers to Fuzzy XPath Queries

Data heterogeneity in XML repositories can be tackled by giving users the possibility to obtain approximate answers to their queries. In this setting, several approaches for XPath queries have been defined in the literature. In particular, fuzzy XPath queries have been recently introduced as a formalism to provide users with a clear understanding of the approximations that the query evaluation process introduces in the answers. However, in many cases, users are not a-priori aware of the maximum approximation degree they would allow in the answers; rather, they are interested in obtaining the first k answers ranked according to their approximation degrees. In this paper we investigate the problem of top-k fuzzy XPath querying, propose a query language and its associated semantics, and discuss query evaluation.

On the expressiveness of generalization rules for XPath query relaxation

The problem of defining suitable rewriting mechanisms for XML query languages to support approximate query answering has received a great deal of attention in the last few years, owing to its practical impact in several scenarios. For instance, in the typical scenario of distributed XML data without a shared data scheme, accomplishing the extraction of the information of interest often requires queries to be rewritten into relaxed ones, in order to adapt them to the schemes adopted in the different sources. In this paper, rewriting systems for a wide fragment of XPath (which is the core of several languages for manipulating XML data) are investigated, and a general form of rewriting rules (namely, generalization rules) is considered, which subsumes the forms adopted in the most well-known rewriting systems. Specifically, the expressiveness of rewriting systems based on this form of rules is characterized: on the one hand, it is shown that rewriting systems based on generalization rules are incomplete w.r.t. containment (thus, traditional rewriting mechanisms do not suffice to rewrite a query into any more general one). On the other hand, it is also shown that the expressiveness of state-of-the-art rewriting systems can be improved by employing rewriting primitives as simple as those traditionally used, which enable any query to be relaxed into every more general one related to it via homomorphism.

DART: a data acquisition and repairing tool

An architecture is proposed providing robust data acquisition facilities from input documents containing tabular data. This architecture is based on a data-repairing framework exploiting integrity constraints defined on the input data to support the detection and the repair of inconsistencies in the data arising from errors occurring in the acquisition phase. In particular, a specific but expressive form of integrity constraints (steady aggregate constraints) is defined which enables the computation of a repair to be expressed as a mixed integer linear programming problem.

Schema-based Web wrapping

An effective solution to automate information extraction from Web pages is represented by wrappers. A wrapper associates a Web page with an XML document that represents part of the information in that page in a machine-readable format. Most existing wrapping approaches have traditionally focused on how to generate extraction rules, while they have ignored potential benefits deriving from the use of the schema of the information being extracted in the wrapper evaluation. In this paper, we investigate how the schema of extracted information can be effectively used in both the design and evaluation of a Web wrapper. We define a clean declarative semantics for schema-based wrappers by introducing the notion of (preferred) extraction model, which is essential to compute a valid XML document containing the information extracted from a Web page. We developed the SCRAP (SChema-based wRAPper for web data) system for the proposed schema-based wrapping approach, which also provides visual support tools to the wrapper designer. Moreover, we present a wrapper generalization framework to profitably speed up the design of schema-based wrappers. Experimental evaluation has shown that SCRAP wrappers are not only able to successfully extract the required data, but also they are robust to changes that may occur in the source Web pages.