Wyniki wyszukiwania - BazTech

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A Novel System Architecture for an Improved Self-care Solution – Conceptual Design and Key Components

Santos Patrick, Ramos Jorge, Seabra Eduardo, Castro José

Journal of Telecommunications and Information Technology

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2020

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nr 4

88--97

EN

The high penetration rate that mobile devices enjoy in to day’s society has facilitated the creation of new digital services, with those offered by operators and content providers standing out. However, even this has failed to encourage consumers to express positive opinions on telecommunication services, especially when compared with other sectors. One of the main reasons of the mistrust shown is the low level of quality of customer service provided an area that generates high costs for the operators themselves, due to the high number of people employed at call centers in order to handle the volume of calls received. To face these challenges, operators launched self-care applications in order to provide customers with a tool that would allow them to autonomously manage the services they have subscribed. In this paper, we present an architecture that provides customized information to customers – a solution that is separate from mobile operating systems and communication technologies.

2

Building semantic user profile for polish web news portal

Misztal-Radecka J.

Computer Science

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2018

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Vol. 19 (3)

307–-332

EN

The aim of this research is to construct meaningful user profiles that are the most descriptive of user interests in the context of the media content that they browse. We use two distinct state-of-the-art numerical text-representation techniques: LDA topic modeling and Word2Vec word embeddings. We train our models on the collection of news articles in Polish and compare them with a model built on a general language corpus. We compare the performance of these algorithms on two practical tasks. First, we perform a qualitative analysis of the semantic relationships for similar article retrieval, and then we evaluate the predictive performance of distinct feature combinations for user gender classification. We apply the algorithms to the real-world dataset of Polish news service Onet. Our results show that the choice of text representation depends on the task –Word2Vec is more suitable for text comparison, especially for short texts such as titles. In the gender classification task, the best performance is obtained with a combination of features: topics from the article text and word embeddings from the title.

3

Application of multi-criteria analysis based on individual psychological profile for recommender systems

Rafalak M., Granat J., Wierzbicki A. P.

Computer Science

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2016

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Vol. 17 (4)

503--517

EN

This paper presents a novel approach for user classification exploiting multi- criteria analysis. This method is based on measuring the distance between an observation and its respective Pareto front. The obtained results show that the combination of the standard KNN classification and the distance from Pareto fronts gives satisfactory classification accuracy – higher than the accuracy ob- tained for each of these methods applied separately. Conclusions from this study may be applied in recommender systems where the proposed method can be implemented as the part of the collaborative filtering algorithm.

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Application of knowledge discovery methods to user profiling

Bembenik R., Chrabąszcz M., Gołębski M.

Archiwum Informatyki Teoretycznej i Stosowanej

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2003

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T. 15, z. 4

343-357

EN

The paper presents topics pertaining to user profiling. Various systems creating such profiles are shown. Most frequently used method of word extraction TF-IDF is discussed as well as document and profile representation. Classification of filtering systems is presented and classification of learning mechanisms employed by different systems. All discussed systems are presented according to learning mechanisms used.

PL

Referat prezentuje zagadnienia związane z tworzeniem profilów użytkowników. Pokazano różne systemy tworzące takie profile. Omówiono najczęściej wykorzystywaną metodę ekstrakcji słów TF-IDF oraz reprezentację dokumentów i profilów. Przedstawiono podział systemów filtrujących oraz podział mechanizmów uczenia się wykorzystywany przez różne systemy. Wszystkie omawiane systemy przedstawiono w zależności od stosowanych w nich metod uczenia się.