Towards experience management for Search Engine Optimisation

Websites of Small and Medium-sized Enterprises (SMEs) can gain an added advantage by getting listed in the search engine’s results page during the search sessions of the searchers. The Search Engine Optimisation (SEO) enables websites to become visible in search engines during search sessions for its featured products or services. It generates additional revenue for the websites. SEO is a complex technique. Its knowledge and experience gained from optimising websites in the past is highly valuable and applicable to optimise websites. This paper dis- cusses the problem of optimisation of websites based on the experience gained by the authors from optimisation of several case study websites. Process models have been generated in order to capture experience of implementing essential elements of SEO and to explain the procedure of implementation of the fundamental on-page SEO techniques that yielded results for the case study websites

Data literacy in the smart university approach

Equipping classrooms with inexpensive sensors for data collection can provide students and teachers with the opportunity to interact with the classroom in a smart way. In this paper two approaches to acquiring contextual data from a classroom environment are presented. We further present our approach to analysing the collected room usage data on site, using low cost single board computer, such as a Raspberry Pi and Arduino units, performing a significant part of the data analysis on-site. We demonstrate how the usage data was used to model specifcic room usage situation as cases in a Case-based reasoning (CBR) system. The room usage data was then integrated in a room recommender system, reasoning on the formalised usage data, allowing for a convenient and intuitive end user experience based on the collected raw sensor data. Having implemented and tested our approaches we are currently investigating the possibility of using (XML)Schema-informed compression to enhance the security and efficiency of the transmission of a large number of sensor reports generated by interpreting the raw data on-site, to our central data sink. We are investigating this new approach to usage data transmission as we are aiming to integrate our on-going work into our vision of the Smart University to ensure and enhance the Smart University's data literacy

Two-phased knowledge formalisation for hydrometallurgical gold ore process recommendation and validation

This paper describes an approach to externalising and formalising expert knowledge involved in the design and evaluation of hydrometallurgical process chains for gold ore treatment. The objective was to create a case-based reasoning application for recommending and validating a treatment process of gold ores. We describe a twofold approach. Formalising human expert knowledge about gold mining situations enables the retrieval of similar mining contexts and respective process chains, based on prospection data gathered from a potential gold mining site. Secondly, empirical knowledge on hydrometallurgical treatments is formalised. This enabled us to evaluate and, where needed, redesign the process chain that was recommended by the first aspect of our approach. The main problems with formalisation of knowledge in the domain of gold ore refinement are the diversity and the amount of parameters used in literature and by experts to describe a mining context. We demonstrate how similarity knowledge was used to formalise literature knowledge. The evaluation of data gathered from experiments with an initial prototype workflow recommender, Auric Adviser, provides promising results

Evaluating patterns of national and international collaboration in Cuban science using bibliometric tools

Purpose -- The purpose of this paper is to explore the hypothesis that collaboration was a key characteristic of Cuban science to maintain their scientific capacity during a period of economic restrictions and an important feature of Cuban science policy and practice for the benefit of society. Design/methodology/approach -- Collaboration was studied through Cuban scientific publications listed in PubMed for the period 1990-2010. The search was carried out using the advanced search engine of PubMed indicating oCubaW in the affiliation field. To identify participating institutions a second search was performed to find the affiliations of all authors per article through the link to the electronic journal. A data set was created to identify institutional publication patterns for the surveyed period. Institutions were classified in three categories according to their scientific production as Central, Middle or Distal: the pattern of collaboration between these categories was analysed. Findings -- Results indicate that collaboration between scientifically advanced institutions (Central) and a wide range of national institutions is a consequence of the social character of science in Cuba in which cooperation prevails. Although this finding comes from a limited field of biomedical science it is likely to reflect Cuban science policy in general. Originality/value -- Using bibliometric tools the study suggests that Cuban science policy and practice ensure the application of science for social needs by harnessing human resources through national and international collaboration, building in this way stronger scientific capacity

Managing search engine optimisation experience using the INRECA methodology

This paper describes the reuse of Search Engine Optimisation (SEO) experience. The SEO domain is characterised by more than 200 factors leading to an obscurity of important factors. Such complex domains require experience-knowledge to enable the novice users adopt the domain. The Case Based Reasoning (CBR) approach is well suited to train new users in using this relatively new SEO technique to improve the visibility of their websites. Based on the principle of similarity, CBR enables the solution of similar recurring SEO problems for optimising websites for search engines. New users can effectively rely on SEO experience knowledge to solve new problems. Moreover, SEO techniques follow a similar procedure of implementation. Such procedural knowledge can be generalised and stored for future reference. For this purpose an experience base has been created to store SEO experience knowledge based on the principle of INRECA methodology. The experience is described using software process models. Until now the INRECA experience base has stored CBR system building experience. This research has extended the INRECA methodology for storing and retrieving SEO experience, taking into account the dynamic nature of the domain of SEO. An experiment illustrates the approach

Approaches to the use of sensor data to improve classroom experience

quipping classrooms with inexpensive sensors can enable students and teachers with the opportunity to interact with the classroom in a smart way. In this paper an approach to acquiring contextual data from a classroom environment, using inexpensive sensors, is presented. We present our approach to formalising the usage data. Further we demonstrate how the data was used to model specific room usage situation as cases in a Case-based reasoning (CBR) system. The room usage data was than integrated in a room recommendations system, reasoning on the formalised usage data. We also detail on our on-going work to integrating the systems presented in this paper into our Smart University vision

Solution mining for specific contextualised problems: towards an approach for experience mining

In this paper we describe the task of automated mining for solutions to highly specific problems. We do so under the premise of mapping the split view on context, introduced by Brézillon and Pomerol, onto three different levels of abstraction of a problem domain. This is done to integrate the notion of activity or focus and its influence on the context into the mining for a solution. We assume that a problem's context describes key characteristics to be decisive criteria in the mining process to mine successful solutions for it. We further detail on the process of a chain of sub problems and their foci adding up to a meta problem solution and how this can used to mine for such solutions. Through a guiding example we introduce basic steps of the solution mining process and common aspects we deem interesting to be analysed closer in upcoming research on solution mining. We further examine the possible integration of these newly established outlines for automatic solution mining for highly specific problems into a SEASALTexp, a currently developed architecture for explanation-aware extraction and case-based processing of experiences from Internet communities. We thereby gained first insights in issues occurring while trying to integrate automatic solution mining

Knowledge modelling with the open source tool myCBR

Building knowledge intensive Case-Based Reasoning applications requires tools that support this on-going process between domain experts and knowledge engineers. In this paper we will introduce how the open source tool myCBR 3 allows for flexible knowledge elicitation and formalisation form CBR and non CBR experts. We detail on myCBR 3 's versatile approach to similarity modelling and will give an overview of the Knowledge Engineering workbench, providing the tools for the modelling process. We underline our presentation with three case studies of knowledge modelling for technical diagnosis and recommendation systems using myCBR 3

Implementation of similarity measures for event sequences in myCBR

The computation of the similarities between event sequences is important for many fields because many activities follow a sequential order. For instance, an industrial plan that triggers different types of alarms due to detected event sequences or the treatment sequence that a patient receives while he/she is hospitalized. With the appropriate tools and techniques to compute the similarity between two event sequences we may be able to detect patterns or regularities in event data and so be able to perform predictions or recommendations based on detected similar sequences. The present work is intended to describe the implementation of two event sequence similarity measures in myCBR, with the purpose of creating a similarity measurement approach for complex domains that employ the use of event sequences. Besides, an initial experimentation is performed in order to study if the proposed measures and measurement approach are able to predict future situations based on similar event sequences