The main idea of filter methods in feature selection is constructing a feature-assessing criterion and searching for feature subset that optimizes the criterion. The primary principle of designing such criterion is to capture the relevance between feature subset and the class as precisely as possible. It would be difficult to compute the relevance directly due to the computation complexity when the size of feature subset grows. As a result, researchers adopt approximate strategies to measure relevance. Though these strategies worked well in some applications, they suffer from three problems: parameter determination problem, the neglect of feature interaction information and overestimation of some features. We propose a new feature selection algorithm that could compute mutual information between feature subset and the class directly without deteriorating computation complexity based on the computation of partitions. In light of the specific properties of mutual information and partitions, we propose a pruning rule and a stopping criterion to accelerate the searching speed. To evaluate the effectiveness of the proposed algorithm, we compare our algorithm to the other five algorithms in terms of the number of selected features and the classification accuracies on three classifiers. The results on the six synthetic datasets show that our algorithm performs well in capturing interaction information. The results on the thirteen real world datasets show that our algorithm selects less yet better feature subset.

We propose a novel representation called Feature Interaction Descriptor (FIND) to capture high-level properties of object appearance by computing pairwise interactions of adjacent region-level features. In order to deal with pedestrian detection task, we employ localized oriented gradient histograms as region-level features and measure interactions between adjacent histogram elements with a suitable histogram-similarity function. The experimental results show that our descriptor improves upon HOG significantly and outperforms related high-level features such as GLAC and CoHOG.

This paper presents a framework for formalizing and detecting feature interactions (FIs) in the emerging smart home domain. We first establish a model of home network system (HNS), where every networked appliance (or the HNS environment) is characterized as an object consisting of properties and methods. Then, every HNS service is defined as a sequence of method invocations of the appliances. Within the model, we next formalize two kinds of FIs: (a) appliance interactions and (b) environment interactions. An appliance interaction occurs when two method invocations conflict on the same appliance, whereas an environment interaction arises when two method invocations conflict indirectly via the environment. Finally, we propose offline and online methods that detect FIs before service deployment and during execution, respectively. Through a case study with seven practical services, it is shown that the proposed framework is generic enough to capture feature interactions in HNS integrated services. We also discuss several FI resolution schemes within the proposed framework.

In this paper, we propose an unbounded model checking method for feature interaction verification for telecommunication systems. Unbounded model checking is a SAT-based verification method and has attracted recent attention as a powerful approach. The interpolation-based approach is one of the most promising unbounded model checking methods and has been proven to be effective for hardware verification. However, the application of unbounded model checking to asynchronous systems, such as telecommunication systems, has rarely been practiced. This is because, with the conventional encoding, the behavior of an asynchronous system can only be represented as a large propositional formula, thus resulting in large computational cost. To overcome this problem we propose to use a new scheme for encoding the behavior of the system and adapt the unbounded model checking algorithm to this encoding. By exploiting the concurrency of an asynchronous system, this encoding scheme allows a very concise formula to represent system's behavior. To demonstrate the effectiveness of our approach, we conduct experiments where 21 pairs of telecommunication services are verified using several methods including ours. The results show that our approach exhibits significant speed-up over unbounded model checking using the traditional encoding.

This paper proposes an algorithm for detecting 3-way interactions. As far as the authors know, this is the first proposal ever made for a detection algorithm of 3-way interactions. In this paper, by analyzing examples, the mechanism of 3-way interactions is clarified and a detection algorithm of 3-way interactions is proposed. Namely the proposed detection algorithm is heuristic. To evaluate the algorithm, we implemented a detection system based on the proposed algorithm and applied it to 12 services, and 82 3-way interactions were detected. This shows the proposed algorithm is effective.

Feature interaction is the term used in telephony systems to refer to inconsistent conflict between multiple communication services. Feature interaction is considered a major obstacle to developing reliable telephony systems and many approaches have been explored to resolve it. In this paper we present an automatic method for detecting latent feature interaction in service specifications. This method uses bounded model checking as its basis. The basic idea behind bounded model checking is to reduce the detection problem to the propositional satisfiability (SAT) decision problem. For asynchronous systems like telecommunication systems, however, traditional bounded model checking does not work well because resulting propositional formulas tend to become very large. We propose a new encoding scheme to overcome this problem and show the effectiveness through comparative experiments with traditional bounded model checking and other model checking methods.

Services that operate normally, independently, will behave differently when simultaneously initiated with another service. This behavior is called a feature interaction. A feature interaction, where the next state can not be determined uniquely for one event, is called a non-determinacy feature interaction. To detect the interaction, judgment has to be made as to whether the state, where the non-determinacy occurs, is reachable from the initial state or not. For the judgment, many methods have been proposed. But, still now, it is required huge computation time to judge the reachability. This paper proposes a new method to test the reachability using a little knowledge elicited beforehand. By using the proposed method computation time was reduced drastically. Besides, by applying the proposed method to a benchmark, the proposed method was confirmed to be effective and reasonable.

This paper proposes a method of automatically eliciting knowledge which is used to detect feature interactions in telecommunication services. With conventional methods, the knowledge is provided manually. With the proposed method, the knowledge is automatically elicited as service constraints. In telecommunication systems, when a new service is added, new state transitions are created. In case of new service, the new state should be reached in the state transitions. On the other hand, some states of existing services should not be reached. These constraints can be considered as knowledge for detecting feature interactions. This paper also proposes a scenario for detecting feature interactions using elicited knowledge. This scenario was confirmed as effective.

Feature interaction detection determines whether interactions occur or not between the new and existing telecommunication services. Most of conventional detection methods on state transition model utilize an exhaustive search. The exhaustive search is fundamentally very powerful in the sense that all interactions are exactly detected. However, it may suffer from the state explosion problem due to the exponential growth of the number of states in the model when the number of users and the number of features increase. In order to cope with this problem, we propose a new detection method using a state reduction technique. By means of a symmetric relation, called permutation symmetry, we succeed in reducing the size of the model while preserving the necessary information for the interaction detection. Experimental evaluation shows that, for practical interaction detection with three users, the proposed method achieves about 80% reduction in space and time, and is more scalable than the conventional ones especially for the increase of the number of users in the service.

Despite the fact that the necessity of FDT (formal description techniques) had been emphasized, many approaches to verifying feature interactions were insufficient. This paper proposes formal definitions for feature interactions which can occur when telecommunication services specified independently are operated in parallel. Seven types of feature interactions are defined formally.

Service interaction resolution is an important study subject to realize a network supporting various advanced communication services. This paper proposes service interaction resolution by service node connected with the communication network via the user-network interface. By executing various advanced services on the service node, service interactions can be efficiently resolved without adding new functions to the existing network. In other words, the service node enables a unified execution control of all the services including those for the originating side and those for the terminating side. This prevents the signalling system and the signalling procedure from being expanded to resolve service interactions. Moreover, the interactions between the services initiated at the conversation active state can be resolved by the service node equipped with function of receiving plural types of in-band signals. This avoids functional expansion of the switching systems in the network. In this paper, feasibility of the proposed resolution scheme is proved by showing a structure of the service node and a detailed procedure to resolve interactions on that service node. In the proposed service node, the application part is divided into basic call processing part and service processing part, and the basic call processing part is represented by three kinds of basic call processing state models. The proposed method for resolving service interactions can control services execution with high flexibility by using feature interaction table.