9144862
Rules and fuzzy rules in text: concept, extraction and usage
Several concepts and techniques have been imported from other disciplines such as Machine Learning and Artificial Intelligence to the field of textual data. In this paper, we focus on the concept of rule and the management of uncertainty in text applications. The different structures considered for the construction of the rules, the extraction of the knowledge base and the applications and usage of these rules are detailed. We include a review of the most relevant works of the different types of rules based on their representation and their application to most of the common tasks of Information Retrieval such as categorization, indexing and classification.
44387886
Fuzzy logic or Lukasiewicz logic: A clarification
Abstract We discuss some issues on fuzzy logic developed by Pavelka [Z. Math. Logic 25 (1979) 45–52, 119–134, 447–464] vs. the many-valued Lukasiewicz's logic. The focus is on the proper choice of fuzzy implication operations, a question which has been addressed many times in the fuzzy research literature. Pavelka had shown in 1979 that the only natural way of formalizing fuzzy logic for truth values in the unit interval [0, 1] is by using Lukasiewicz's implication operator a → b = min {1, 1 - a + b } or some isomorphic form of it. Many other papers around the same time had attempted to formulate alternative definitions for a → b by giving intuitive justifications. There continues to be some confusion, however, even today about the right notion of fuzzy logic. Much of this confusion lies in the use of improper “an” (“or”) and the “not” operations and a misunderstanding of some of the key differences between “proofs” or inferencing in fuzzy logic and those in Lukasiewicz's logic. We point out the need for defining the strong conjunction operator “⊗” in connection with fuzzy Modus-ponens rule and why we do not need the fuzzy Syllogism inference rule. We formulate two requirements of the fuzzy implication operator, which are satisfied by Lukasiewicz's a → b , but which fail for many of the alternative definitions for “→”.
36997041
The Logic of Only Knowing as a Unified Framework for Non-Monotonic Reasoning
We propose to use the logic of only knowing (OL) by Levesque [10] as a unified framework that encompasses various non-monotonic formalisms and logic programming. OL is a modal logic which can be used to formalize an agent's introspective reasoning and to answer epistemic queries to databases. The OL logic allows one to formally express the statement “α is all I know” (in symbols, Oα) and to perform inferencing based on only-knowing, which is very useful for commonsense reasoning. Another nice thing about the OL logic is that it has a clear model-theoretic semantics and a simple proof theory, which is sound for the quantificational case, and both sound and complete for the prepositional case. We establish the relations between OL and various non-monotonic logics (such as default logic, circumscription) and logic programming, thus extending the existing works relating the OL logic with other non-monotonic reasoning formalisms (e.g., Levesque showed that autoepistemic logic can be embeded in OL). This is accomplished by finding the connection between OL and MBNF, the logic of Minimal Belief and Negation as Failure proposed by Lifschitz [12, 13], which is known to have close relationship with logic programming and other non-monotonic logics. Our results show that OL can be used as a unified framework to compare different non-monotonic formalisms based on the same domain.
27409853
The Strong Semantics for Logic Programs
Recently, the well-founded semantics of a logic program P has been strengthened to the well-founded semantics-by-case (WF C ) and then again to the extended well-founded semantics (WF E ). An important concept used in both WF C and WF E is that of derived rules. We extend the notion of derived rules by adding a new type of derivation and define the strong semantics of P, which has the following important property, known as the GCWA-property: if an atom p = false in all minimal models of P, then p = false in the strong semantics of P. In general, the WF C -semantics and the WF E -semantics do not have the GCWA-property. If we first apply the WF E -semantics to P and then apply the strong semantics to a suitably simplified form of P based on its WF E -semantics, then the resulting semantics is stronger than the WF E -semantics and has the GCWA-property.
27866706
A New Method of Circumscribing Beliefs: The Propositional Case
We propose here a new notion of a minimal model for forming circumscription in belief-logic by incorporating the notion of minimal models in the prepositional logic. This results in a new circumscription operation for belief-formulas than the one considered in [4-6]. An important feature of the new circumscription operation is its close relationship with the circumscription of prepositional formulas. For instance, we have CIRC[Bp] = B(CIRC[p]), where p is a prepositional formula. We give several examples to show that the new notion of circumscription fits quite well with intuition.
28375225
User-centered indexing for adaptive information access
We are focusing on information access tasks characterized by large volume of hypermedia connected technical documents, a need for rapid and effective access to familiar information, and long-term interaction with evolving information. The problem for technical users is to build and maintain a personalized task-oriented model of the information to quickly access relevant information. We propose a solution which provides user-centered adaptive information retrieval and navigation. This solution supports users in customizing information access over time. It is complementary to information discovery methods which provide access to new information, since it lets users customize future access to previously found information. It relies on a technique, called Adaptive Relevance Network, which creates and maintains a complex indexing structure to represent personal user's information access maps organized by concepts. This technique is integrated within the Adaptive HyperMan system, which helps NASA Space Shuttle flight controllers organize and access large amount of information. It allows users to select and mark any part of a document as interesting, and to index that part with user-defined concepts. Users can then do subsequent retrieval of marked portions of documents. This functionality allows users to define and access personal collections of information, which are dynamically computed. The system also supports collaborative review by letting users share group access maps. The adaptive relevance network provides long-term adaptation based both on usage and on explicit user input. The indexing structure is dynamic and evolves over time. Learning and generalization support flexible retrieval of information under similar concepts. The network is geared towards more recent information access, and automatically manages its size in order to maintain rapid access when scaling up to large hypermedia space. We present results of simulated learning experiments.
18675643
Tight Bound on Johnson's Algorithm for Maximum Satisfiability
We present new techniques that give a more thorough analysis on Johnson's classical algorithm for the Maximum Satisfiability problem. In contrast to the common belief for two decades that Johnson's Algorithm has performance ratio 1/2, we show that the performance ratio is 2/3 and that this bound is tight. Moreover, we show that simple generalizations of Johnson's algorithm do not improve the performance ratio bound 2/3.
204766
Scalability, fidelity, and containment in the potemkin virtual honeyfarm
The rapid evolution of large-scale worms, viruses and bot-nets have made Internet malware a pressing concern. Such infections are at the root of modern scourges including DDoS extortion, on-line identity theft, SPAM, phishing, and piracy. However, the most widely used tools for gathering intelligence on new malware -- network honeypots -- have forced investigators to choose between monitoring activity at a large scale or capturing behavior with high fidelity. In this paper, we describe an approach to minimize this tension and improve honeypot scalability by up to six orders of magnitude while still closely emulating the execution behavior of individual Internet hosts. We have built a prototype honeyfarm system, called Potemkin, that exploits virtual machines, aggressive memory sharing, and late binding of resources to achieve this goal. While still an immature implementation, Potemkin has emulated over 64,000 Internet honeypots in live test runs, using only a handful of physical servers.
563848
An efficient parameterized algorithm for m-set packing
We present an efficient parameterized algorithm solving the Set Packing problem, in which we assume that the size of the sets is bounded by m. In particular, if the size m of the sets is bounded by a constant, then our algorithm is fixed-parameter tractable. For example, if the size of the sets is bounded by 3, then our algorithm runs in time O((5.7k)kn).
12280706
A distributed multi-agent system for collaborative information management and sharing
In this paper, we present DIAMS, a system of distributed, collaborative agents to help users access, manage, share and exchange information. A DIAMS personal agent helps its owner find information most relevant to current needs. It provides tools and utilities for users to manage their information repositories with dynamic organization and virtual views. Flexible hierarchical display is integrated with indexed query search to support effective information access. Automatic indexing methods are employed to support user queries and communication between agents.