Probabilistic knowledge bases

Abstract

We define a new fixpoint semantics for rule-based reasoning in the presence of weighted information. The semantics is illustrated on a real-world application requiring such reasoning. Optimizations and approximations of the semantics are shown so as to make the semantics amenable to very large scale real-world applications. We finally prove that the semantics is probabilistic and reduces to the usual fixpoint semantics of stratified Datalog if all information is certain. We implemented various knowledge discovery systems which automatically generate such probabilistic decision rules. In collaboration with a bank in Hong Kong we use one such system to forecast currency exchange rates.Index Terms-Axiomatic probability theory, data mining, incomplete information, knowledge discovery in databases, query optimization and approximation, stratified Datalog.

Daily prediction of Major Stock Indices from Textual WWW Data

“…3. From the weights and the closing values of the training data, probabilistic rules are generated Wtithrich (1995), Wtithrich (1997). 4.…”

Stock prediction: an event-driven approach based on bursty keywords

“…Wuthrich et al [24] develop an online system for predicting the opening prices of five stock indices, where by combining the weights of the keywords from news articles and the historical closing prices of a particular index, some probabilistic rules are generated using the approach proposed in [25]. Laverenko et al [26] propose a system for predicting the intra day stock price movements by analyzing the contents of the real-time news articles based on a language modeling approach, which is in turn proposed in [26].…”

Lifted First-Order Probabilistic Inference

“…Wüthrich [Wüt95] elaborates on their work, taking into account partial dependencies between clauses. For example, if each of atoms a, b and c has a prior probability of 0.5 and we have two rules p ← a∧b and p ← b∧c, Kiefer and Li will assume the rules independent and assign a probability 0.25 + 0.25 − 0.25 * 0.25 = 0.4375 to p. Wüthrich's system, however, takes into account the fact that b is shared by the clauses and computes instead 0.25 + 0.25 − 0.5 3 = 0.375 (that is, it avoids double counting of the case where the two rules fire at the same time, which occurs only when the three atoms are true at once).…”