1889167
An Extension to GCWA and Query Evaluation for Disjunctive Deductive Databases
We present a simple and intuitive extension GCWAG of the generalized closed world assumption (GCWA) from positive disjunctive deductive databases to general disjunctive deductive databases (with default negation). This semantics is defined in terms of unfounded sets and possesses an argumentation-theoretic characterization. We also provide a top-down procedure for GCWAG, which is sound and complete with respect to GCWAG. We investigate two query evaluation methods for GCWAG: database partition, and database splitting. The basic idea of these methods is to divide the original deductive database into several smaller sub-databases and the query evaluation in the original database is transformed into the problem of query evaluation in smaller or simplified components. We prove that these two methods of query evaluation are all sound with respect to GCWAG.
8617754
Comparisons and computation of well-founded semantics for disjunctive logic programs
Much work has been done on extending the well-founded semantics to general disjunctive logic programs and various approaches have been proposed. However, these semantics are different from each other and no consensus is reached about which semantics is the most intended. In this article, we look at disjunctive well-founded reasoning from different angles. We show that there is an intuitive form of the well-founded reasoning in disjunctive logic programming which can be characterized by slightly modifying some existing approaches to defining disjunctive well-founded semantics, including program transformations, argumentation, unfounded sets (and resolution-like procedure). By employing the techniques developed by Brass and Dix in their transformation-based approach, we also provide a bottom-up procedure for this semantics. The significance of our work is not only in clarifying the relationship among different approaches, but also shed some light on what is an intended well-founded semantics for disjunctive logic programs.
5228937
Merging and Aligning Ontologies in dl-Programs
The language of dl-programs is a latest effort in developing an expressive representation for Web-based ontologies. It allows to build answer set programming (ASP) on top of description logic and thus some attractive features of ASP can be employed in the design of the Semantic Web architecture. In this paper we first generalize dl-programs by allowing multiple knowledge bases and then accordingly, define the answer set semantics for the dl-programs. A novel technique called forgetting is developed in the setting of dl-programs and applied to ontology merging and aligning.
384033
Forgetting in Managing Rules and Ontologies
The language of HEX-programs under the answer-set semantics is designed for interoperating with heterogeneous sources via external atoms and for meta-reasoning via higher-order literals in the context of the semantic Web. As an important technique in managing knowledge bases, the notion of forgetting has received increasing interest in the knowledge-representation area. In this paper, we introduce a semantics-based theory of forgetting for HEX-programs and, in turn, for a class of OWL/RDF(S) ontologies which allows to fully employ semantic information in managing ontologies like editing, merging, aligning, and redundancy removal
15783530
A Top-Down Procedure for Disjunctive Well-Founded Semantics
Skepticism is one of the most important semantic intuitions in artificial intelligence. The semantics formalizing skeptical reasoning in (disjunctive) logic programming is usually named well-founded semantics. However, the issue of defining and computing the well-founded semantics for disjunctive programs and databases has proved to be far more complex and difficult than for normal logic programs. The argumentation-based semantics WFDS is among the most promising proposals that attempts to define a natural well-founded semantics for disjunctive programs. In this paper, we propose a top-down procedure for WFDS called D-SLS Resolution, which naturally extends the Global SLS-resolution and SLI-resolution. We prove that D-SLS Resolution is sound and complete with respect to WFDS. This result in turn provides a further yet more powerful argument in favor of the WFDS.
1885288
A Theory of Forgetting in Logic Programming
The study of forgetting for reasoning has attracted considerable attention in AI. However, much of the work on forgetting, and other related approaches such as independence, irrelevance and novelty, has been restricted to the classical logics. This paper describes a detailed theoretical investigation of the notion of forgetting in the context of logic programming. We first provide a semantic definition of forgetting under the answer sets for extended logic programs. We then discuss the desirable properties and some motivating examples. An important result of this study is an algorithm for computing the result of forgetting in a logic program. Furthermore, we present a modified version of the algorithm and show that the time complexity of the new algorithm is polynomial with respect to the size of the given logic program if the size of certain rules is fixed. We show how the proposed theory of forgetting can be used to characterize the logic program updates.
6416971
Anomalous Payload-Based Network Intrusion Detection
We present a payload-based anomaly detector, we call PAYL, for intrusion detection. PAYL models the normal application payload of network traffic in a fully automatic, unsupervised and very effecient fashion. We first compute during a training phase a profile byte frequency distribution and their standard deviation of the application payload flowing to a single host and port. We then use Mahalanobis distance during the detection phase to calculate the similarity of new data against the pre-computed profile. The detector compares this measure against a threshold and generates an alert when the distance of the new input exceeds this threshold. We demonstrate the surprising effectiveness of the method on the 1999 DARPA IDS dataset and a live dataset we collected on the Columbia CS department network. In once case nearly 100% accuracy is achieved with 0.1% false positive rate for port 80 traffic.
1098870
Hierarchical Document Clustering using Frequent Itemsets
A major challenge in document clustering is the extremely high dimensionality. For example, the vocabulary for a document set can easily be thousands of words. On the other hand, each document often contains a small fraction of words in the vocabulary. These features require special handlings. Another requirement is hierarchical clustering where clustered documents can be browsed according to the increasing specificity of topics. In this paper, we propose to use the notion of frequent itemsets, which comes from association rule mining, for document clustering. The intuition of our clustering criterion is that each cluster is identified by some common words, called frequent itemsets, for the documents in the cluster. Frequent itemsets are also used to produce a hierarchical topic tree for clusters. By focusing on frequent items, the dimensionality of the document set is drastically reduced. We show that this method outperforms best existing methods in terms of both clustering accuracy and scalability.
2174685
Privacy-enhancing personalized web search
Personalized web search is a promising way to improve search quality by customizing search results for people with individual information goals. However, users are uncomfortable with exposing private preference information to search engines. On the other hand, privacy is not absolute, and often can be compromised if there is a gain in service or profitability to the user. Thus, a balance must be struck between search quality and privacy protection. This paper presents a scalable way for users to automatically build rich user profiles. These profiles summarize a user.s interests into a hierarchical organization according to specific interests. Two parameters for specifying privacy requirements are proposed to help the user to choose the content and degree of detail of the profile information that is exposed to the search engine. Experiments showed that the user profile improved search quality when compared to standard MSN rankings. More importantly, results verified our hypothesis that a significant improvement on search quality can be achieved by only sharing some higher-level user profile information, which is potentially less sensitive than detailed personal information.
12098916
Binary decision diagram with minimum expected path length
We present methods to generate a Binary Decision Diagram (BDD) with minimum expected path length. A BDD is a generic data structure which is widely used in several fields. One important application is the representation of Boolean functions. A BDD representation enables us to evaluate a Boolean function: Simply traverse the BDD from the root node to the terminal node and retrieve the value in the terminal node. For a BDD with minimum expected path length will be also minimized the evaluation time for the corresponding Boolean function. Three efficient algorithms for constructing BDDs with minimum expected path length are proposed.
52857819
QUICK: graphical user interface to multiple databases
Formulating queries to access multiple databases can be a formidable task, especially when many terms from various databases and complex constraints are involved. To specify a multidatabase query, the user usually has to search through documents for exact database terms and learn the multidatabase language. The report presents QUICK (QUery Interface to CPL-Kleisli), a graphical user interface to multiple databases, CPL is a high-level multidatabase language built on top of an open query system Kleisli. QUICK allows users to handle overwhelming information from different data sources in an intuitive and uniform manner. The query specification is reduced to specifying user's terms in his/her own world, selecting paths and specifying constraints in a graph. QUICK is able to automatically generate a CPL query that corresponds to the user's intent.