We identify a shortcoming of a standard positive-only clause evaluation function within the context of learning biological grammars. To overcome this shortcoming we propose L-modification, a modification to this evalu...
详细信息
ISBN:
(纸本)9783540859277
We identify a shortcoming of a standard positive-only clause evaluation function within the context of learning biological grammars. To overcome this shortcoming we propose L-modification, a modification to this evaluation function such that the lengths of individual examples are considered. We use a set of bio-sequences known as neuropeptide precursor middles (NPP-middles). Using L-modification to learn from these NPP-middles results in induced grammars that have a better performance than that achieved when using the standard positive-only clause evaluation function. We also show that L-modification improves the performance of induced grammars when learning on short, medium or long NPPs-middles. A potential disadvantage of L-modification is discussed. Finally, we show that, as the limit on the search space size increases, the greater is the increase in predictive performance arising from L-modification.
this paper gives a brief overview of the international workshop on semantic technologies in system maintenance. It describes a number of semantic technologies (e.g., ontologies, text mining, and knowledge integration ...
详细信息
this paper gives a brief overview of the international workshop on semantic technologies in system maintenance. It describes a number of semantic technologies (e.g., ontologies, text mining, and knowledge integration techniques) and identifies diverse tasks in software maintenance where the use of semantic technologies can be beneficial, such as traceability, system comprehension, software artifact analysis, and information integration.
Although object-oriented programming promotes reusable and well factored entity decomposition, industrial software often shows traces of lack of object-oriented design and procedural thinking. this results in domain e...
详细信息
Although object-oriented programming promotes reusable and well factored entity decomposition, industrial software often shows traces of lack of object-oriented design and procedural thinking. this results in domain entity scattered and tangled code. this is often true in data intensive applications. Aspect mining techniques search for various patterns of scattered and tangled code pertaining to crosscutting concerns. However, in the presence of non-abstracted domain logic, the crosscutting concerns identified are inaccurately related to aspects since lack of 00 abstraction introduces false positives. this paper identifies the difficulty of identifying crosscutting concerns in systems lacking elementary object-oriented structure. It presents an approach classifying various crosscutting concerns. We report our experience on an industrial software system.
Reusing syntax specifications without embedded arbitrary semantic actions is straightforward because the semantic analysis phases of new applications can feed off trees or other intermediate structures constructed by ...
详细信息
Reusing syntax specifications without embedded arbitrary semantic actions is straightforward because the semantic analysis phases of new applications can feed off trees or other intermediate structures constructed by the pre-existing parser. the presence of arbitrary embedded semantic actions, however, makes reuse difficult with existing mechanisms such as grammar inheritance and modules. this short paper proposes a mechanism based upon prototype grammars that automatically pushes changes from prototypes to derived grammars even in the presence of semantic actions. the prototype mechanism alone would be unsuitable for creating a new grammar from multiple preexisting grammars. When combined with grammar composition, however, the prototype mechanism would improve grammar reuse because imported pre-existing grammars could be altered to suit each new application.
Reasoning about changes caused by the execution of actions has long been at the center of attention of researchers in the area of logic-based AI. logical properties of causal dependencies turned out to be similar to p...
详细信息
ISBN:
(纸本)9783540738466
Reasoning about changes caused by the execution of actions has long been at the center of attention of researchers in the area of logic-based AI. logical properties of causal dependencies turned out to be similar to properties of rules in logic programs. this fact allows us to apply methods of logicprogramming to computational problems related to action and change. Ideas of answer set programming, based on the concept of a stable model, turned out to be particularly useful. In the past they have been applied primarily to the problem of plan generation. there is now increasing interest also in using logicprogramming for learning action descriptions.
In this paper we present the system ALLPAD for learning logic Programs with Annotated Disjunctions (LPADs). ALLPAD modifies the previous system LLPAD in order to tackle real world learning problems more effectively. T...
详细信息
ISBN:
(纸本)9783540738466
In this paper we present the system ALLPAD for learning logic Programs with Annotated Disjunctions (LPADs). ALLPAD modifies the previous system LLPAD in order to tackle real world learning problems more effectively. this is achieved by looking for an approximate solution rather than a perfect one. ALLPAD has been tested on the problem of classifying proteins according to their tertiary structure and the results compare favorably with most other approaches.
In this paper, we present a probabilistic method of dealing with multi-class classification using Stochastic logic Programs (SLPs), a Probabilistic inductivelogicprogramming (PILP) framework that integrates probabil...
详细信息
ISBN:
(纸本)9783540738466
In this paper, we present a probabilistic method of dealing with multi-class classification using Stochastic logic Programs (SLPs), a Probabilistic inductivelogicprogramming (PILP) framework that integrates probability, logic representation and learning. Multi-class prediction attempts to classify an observed datum or example into its proper classification given that it has been tested to have multiple predictions. We apply an SLP parameter estimation algorithm to a previous study in the protein fold prediction area and a multi-class classification working example, in which logic programs have been learned by inductivelogicprogramming (ILP) and a large number of multiple predictions have been detected. On the basis of several experiments, we demonstrate that PILP approaches (eg. SLPs) have advantages for solving multi-class prediction problems withthe help of learned probabilities. In addition, we show that SLPs outperform ILP plus majority class predictor in both predictive accuracy and result interpretability.
We investigate using the Mercury language to implement and design ILP algorithms, presenting our own ILP system IMP. Mercury provides faster execution than Prolog. Since Mercury is a purely declarative language, run-t...
详细信息
ISBN:
(纸本)9783540738466
We investigate using the Mercury language to implement and design ILP algorithms, presenting our own ILP system IMP. Mercury provides faster execution than Prolog. Since Mercury is a purely declarative language, run-time assertion of induced clauses is prohibited. Instead IMP uses a problem-specific interpreter of ground representations of induced clauses. the interpreter is used both for cover testing and bottom clause generation. the Mercury source for this interpreter is generated automatically from the user's background knowledge using Moose, a Mercury parser generator. Our results include some encouraging results on IMP's cover testing speed, but overall IMP is still generally a little slower than ALEPH.
the ProbLog (probabilistic prolog) language has been introduced in [1], where various algorithms have been developed for solving and approximating ProbLog queries. Here, we define and study the problem of revising Pro...
详细信息
ISBN:
(纸本)9783540738466
the ProbLog (probabilistic prolog) language has been introduced in [1], where various algorithms have been developed for solving and approximating ProbLog queries. Here, we define and study the problem of revising ProbLog theories from examples.
Since the early days of AI, automated reasoning has been a rather elusive goal. In fact, up till the early nineties, general inference beyond hundred variable problems appeared infeasible. Over the last decade, we hav...
详细信息
ISBN:
(纸本)9783540738466
Since the early days of AI, automated reasoning has been a rather elusive goal. In fact, up till the early nineties, general inference beyond hundred variable problems appeared infeasible. Over the last decade, we have witness a qualitative change in the field: current reasoning engines can handle problems with over a million variables and several millions of constraints. I will discuss what led to such a dramatic scale-up, and how progress in reasoning technology has opened up a range of new applications in AI and computer science in general. I will also discuss initial progress on the use of learning techniques in reasoning engines and the remaining challenges for obtaining a true integration of learning and reasoning.
暂无评论