Web Intelligence - Volume 16, issue 4

Authors: Bravo-Marquez, Felipe | Frank, Eibe | Pfahringer, Bernhard

Article Type: Research Article

Abstract: Message-level and word-level polarity classification are two popular tasks in Twitter sentiment analysis. They have been commonly addressed by training supervised models from labelled data. The main limitation of these models is the high cost of data annotation. Transferring existing labels from a related problem domain is one possible solution for this problem. In this paper, we study how to transfer sentiment labels from the word domain to the tweet domain and vice versa by making their corresponding instances compatible. We model instances of these two domains as the aggregation of instances from the other (i.e., tweets are treated as …collections of the words they contain and words are treated as collections of the tweets in which they occur) and perform aggregation by averaging the corresponding constituents. We study two different setups for averaging tweet and word vectors: 1) representing tweets by standard NLP features such as unigrams and part-of-speech tags and words by averaging the vectors of the tweets in which they occur, and 2) representing words using skip-gram embeddings and tweets as the average embedding vector of their words. A consequence of our approach is that instances of both domains reside in the same feature space. Thus, a sentiment classifier trained on labelled data from one domain can be used to classify instances from the other one. We evaluate this approach in two transfer learning tasks: 1) sentiment classification of tweets by applying a word-level sentiment classifier, and 2) induction of a polarity lexicon by applying a tweet-level polarity classifier. Our results show that the proposed model can successfully classify words and tweets after transfer. Show more

Keywords: Sentiment classification, polarity lexicon expansion, Twitter, transfer learning

DOI: 10.3233/WEB-180389

Citation: Web Intelligence, vol. 16, no. 4, pp. 203-220, 2018

Authors: Amad, Mourad | Aïssani, Djamil | Meddahi, Ahmed | Merabet, Aimed | Sekhriou, Noureddine

Article Type: Research Article

Abstract: Lookup services is still a key challenge in all distributed systems and particularly for P2P based services (e.g. distributed SDN node controllers, social networking… ). In these networks, node searching for a specific service or resource has to discover the “best” path to the node offering the requested resource or service. Since P2P networking is implemented at application layer, the given optimized path from a source node to a destination one, in terms of number of hops is not necessarily the best path in terms of physical parameters (e.g. delay, physical proximity ). For this, the lookup process optimization is …still a real challenge in some environments, particularly for delay sensitive services. In this context, various topologies have been proposed in the literature such as: ring, tore, star, hypercub, De Bruijn graph, and skip graph. In this paper, we propose a new approach using Pancake graphs, for structuring the P2P topology in order to optimize the lookup process. The proposed solution is compared to some main existing solutions. Under certain conditions, the simulation results show better performance compared to existing approaches. Show more

Keywords: P2P, Pancake graphs, routing optimization

DOI: 10.3233/WEB-180390

Citation: Web Intelligence, vol. 16, no. 4, pp. 221-232, 2018

Authors: Soetrisno, Yosua Alvin Adi | Sulistyo, Selo | Ferdiana, Ridi | Adji, Teguh Bharata

Article Type: Research Article

Abstract: The development of negative sites brings harm to users of the Internet, especially among teenagers. One way to block these sites is to provide a list of sites that are categorized as negative. However, the problem is that every day new sites appear that have not been listed yet. Therefore an intelligent system that can detect the content and can automatically update the list is needed. Negative content on a website can consist of text, image, and video contents that require different parsing techniques and classifiers to separate and classify such contents. Each classifier produces a probability. Hence, an algorithm …that can combine these probabilities is required. Fusion algorithm can combine the probabilities of text, images, and video contents. However, the algorithm does not work on websites which have an equal proportion of negative and positive images, i.e. grey websites. These websites require specific handling such as a cascade fusion algorithm to change the sensitivity so it can reduce the level of over blocking. The results show that after the modification of the fusion algorithm, the accuracy of the classifier increased from 91.62% to 98.49% because the rate of over blocking could be reduced. Show more

Keywords: Fusion, algorithm, cascade, classification, filtering, parsing

DOI: 10.3233/WEB-180391

Citation: Web Intelligence, vol. 16, no. 4, pp. 233-246, 2018

Article Type: Other

Citation: Web Intelligence, vol. 16, no. 4, pp. 247-247, 2018

Authors: Esfandiari, Babak | Steghöfer, Jan-Philipp

Article Type: Editorial

DOI: 10.3233/WEB-180392

Citation: Web Intelligence, vol. 16, no. 4, pp. 249-249, 2018

Authors: Primiero, Giuseppe | Boender, Jaap

Article Type: Research Article

Abstract: Software management systems need to preserve integrity by the handling, approval, tracking and execution of changes on the packages of the current installation profile. This is a problematic task, which needs to be accounted for both in terms of installation of new packages and removal of conflicting ones. While existing approaches are able to identify dependency satisfaction and conflicts, a broader and efficient approach can be formalised in terms of trust. Positive instances of trust are required by the identification of safely installable packages. Negative trust, a much less explored concept, can be useful to analyse the complementary issue of …packages’ removal both in case of conflicts and of security issues. In this paper we develop a logic of negative trust with two aims: identifying packages that are undesirable in view of the current installation profile; and currently installed packages that become inconsistent with a new intended installation. The logic provides distinct procedures for the identification of either case. We illustrate properties of the calculus, provide a simple working example and offer a translation of the protocol to the Coq proof assistant for verification of its formal correctness. Show more

Keywords: Trust, negative trust, software management, software installation system, uninstall problem

DOI: 10.3233/WEB-180393

Citation: Web Intelligence, vol. 16, no. 4, pp. 251-271, 2018

Authors: Richthammer, Christian | Weber, Michael | Pernul, Günther

Article Type: Research Article

Abstract: Recommender systems are pivotal components of modern Internet platforms and constitute a well-established research field. By now, research has resulted in highly sophisticated recommender algorithms whose further optimization often yields only marginal improvements. This paper goes beyond the commonly dominating focus on optimizing algorithms and instead follows the idea of enhancing recommender systems with reputation data. Since the concept of reputation-enhanced recommender systems has attracted considerable attention in recent years, the main aim of the paper is to provide a comprehensive survey of the approaches proposed so far. To this end, existing work is identified by means of a systematic …literature review and classified according to seven carefully considered dimensions. In addition, the resulting structured analysis of the state of the art serves as a basis for the deduction and discussion of several future research directions. Show more

Keywords: Recommender systems, decision support systems, reputation, trust, reputation-enhanced recommender systems

DOI: 10.3233/WEB-180394

Citation: Web Intelligence, vol. 16, no. 4, pp. 273-286, 2018