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1 – 2 of 2Vasileios Stamatis, Michail Salampasis and Konstantinos Diamantaras
In federated search, a query is sent simultaneously to multiple resources and each one of them returns a list of results. These lists are merged into a single list using the…
Abstract
Purpose
In federated search, a query is sent simultaneously to multiple resources and each one of them returns a list of results. These lists are merged into a single list using the results merging process. In this work, the authors apply machine learning methods for results merging in federated patent search. Even though several methods for results merging have been developed, none of them were tested on patent data nor considered several machine learning models. Thus, the authors experiment with state-of-the-art methods using patent data and they propose two new methods for results merging that use machine learning models.
Design/methodology/approach
The methods are based on a centralized index containing samples of documents from all the remote resources, and they implement machine learning models to estimate comparable scores for the documents retrieved by different resources. The authors examine the new methods in cooperative and uncooperative settings where document scores from the remote search engines are available and not, respectively. In uncooperative environments, they propose two methods for assigning document scores.
Findings
The effectiveness of the new results merging methods was measured against state-of-the-art models and found to be superior to them in many cases with significant improvements. The random forest model achieves the best results in comparison to all other models and presents new insights for the results merging problem.
Originality/value
In this article the authors prove that machine learning models can substitute other standard methods and models that used for results merging for many years. Our methods outperformed state-of-the-art estimation methods for results merging, and they proved that they are more effective for federated patent search.
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Nikolaos Panayiotou and Vasileios Stavrou
This paper aims to construct an assessment framework to establish a maturity model for Web Electronic Services offered at a local government level and investigate the maturity of…
Abstract
Purpose
This paper aims to construct an assessment framework to establish a maturity model for Web Electronic Services offered at a local government level and investigate the maturity of Greek municipalities in the E-Government field, trying to correlate how this is affected by demographic variables.
Design/methodology/approach
An original assessment framework regarding municipal Electronic Services was created based on the literature review. The assessment framework was included in a methodological approach supported by the PROMETHEE II method, as well as by selected statistical methods. The framework and the methodological approach were applied in the case of Greek municipalities.
Findings
The analysis revealed the low maturity level of Greek municipalities in Electronic Services sector. The Greek case study indicated that the proposed framework and methodological approach could provide useful insights to municipalities for the improvement of its E-Government Web services based on their strategic preferences.
Research limitations/implications
The assessment took place only in Greece, assessing all the country's municipalities and conducting research only in the municipalities’ websites. The proposed methodology suggests that the PROMETHEE II multi-criteria decision analysis method can support the assessment of the maturity level of local government entities. Moreover, the combination of the PROMETHEE II–empowered assessment framework with demographic statistical analysis can assist orthological decision-making concerning future investments in Web Electronic Services. The methodology could be a good option for future research efforts (assessments) in municipalities, in Greece and worldwide.
Practical implications
The framework is both easy to use and fairly complete. The fact that the assessment was conducted in all the Greek municipalities makes it much more reliable, as it provides the whole picture. The suggested methodology which includes the proposed framework could be used in the cases of municipalities in other countries to assist future actions concerning the investment in Web Electronic Services.
Originality/value
This study provided a medium-size framework, being both complete and easy to use during the evaluation process of all the municipalities in Greece. In addition, the statistical analysis received data from a decision-making tool to execute the clustering (Cluster analysis is usually performed based on the raw data).
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