Weighted Heuristic Ensemble of Filters

Feature selection has become increasingly important in data mining in recent years due to the rapid increase in the dimensionality of big data. However, the reliability and consistency of feature selection methods (filters) vary considerably on different data and no single filter performs consistently well under various conditions. Therefore, feature selection ensemble has been investigated recently to provide more reliable and effective results than any individual one but all the existing feature selection ensemble treat the feature selection methods equally regardless of their performance. In this paper, we present a novel framework which applies weighted feature selection ensemble through proposing a systemic way of adding different weights to the feature selection methods-filters. Also, we investigate how to determine the appropriate weight for each filter in an ensemble. Experiments based on ten benchmark datasets show that theoretically and intuitively adding more weight to ‘good filters’ should lead to better results but in reality it is very uncertain. This assumption was found to be correct for some examples in our experiment. However, for other situations, filters which had been assumed to perform well showed bad performance leading to even worse results. Therefore adding weight to filters might not achieve much in accuracy terms, in addition to increasing complexity, time consumption and clearly decreasing the stability

Average Scores Integration in Official Star Rating Scheme

Purpose: Evidence suggests that electronic word-of-mouth (eWOM) plays a highly influential role in decision-making when booking hotel rooms. The number of online sources where consumers can obtain information on hotel ratings provided has grown exponentially. Hence, a number of companies have developed average scores to summarize this information and to make it more easily available to consumers. Furthermore, official star rating schemes are starting to provide these commercially developed average scores to complement the information their schemes offer. The purpose of this paper is to examine the robustness of these systems. Design/methodology/approach: Average scores from different systems, and the scores provided by one rating site were collected for 200 hotels and compared. Findings: Findings suggested important differences in the ratings and assigned descriptive word across websites. Research limitations/implications: The results imply that the application of average scores by official organizations is not legitimate and identifies a research gap in the area of consumer and star rating standardization. Originality/value: The paper is of value to the industry and academia related to the examination of rating scales adopted by major online review tourism providers. Evidence of malpractice has been identified and the adoption of this type of scales by official star rating schemes is questioned.Peer reviewe

University of Twente at the TREC 2008 Enterprise Track: using the Global Web as an expertise evidence source

This paper describes the details of our participation in expert search task of the TREC 2007 Enterprise track.\ud This is the fourth (and the last) year of TREC 2007 Enterprise Track and the second year the University of Twente (Database group) submitted runs for the expert nding task. In the methods that were used to produce these runs, we mostly rely on the predicting potential of those expertise evidence sources that are publicly available on the Global Web, but not hosted at the website of the organization under study (CSIRO). This paper describes the follow-up studies\ud complimentary to our recent research [8] that demonstrated how taking the web factor seriously signicantly improves the performance of expert nding in the enterprise

Using the Global Web as an Expertise Evidence Source

This paper describes the details of our participation in expert search task of the TREC 2007 Enterprise track. The presented study demonstrates the predicting potential of the expertise evidence that can be found outside of the organization. We discovered that combining the ranking built solely on the Enterprise data with the Global Web based ranking may produce significant increases in performance. However, our main goal was to explore whether this result can be further improved by using various quality measures to distinguish among web result items. While, indeed, it was beneficial to use some of these measures, especially those measuring relevance of URL strings and titles, it stayed unclear whether they are decisively important

Bilingual Lexicon Extraction from Comparable Corpora as Metasearch

International audienceIn this article we present a novel way of looking at the problem of automatic acquisition of pairs of translationally equivalent words from comparable corpora. We first present the standard and extended approaches traditionally dedicated to this task. We then reinterpret the extended method, and motivate a novel model to reformulate this approach inspired by the metasearch engines in information retrieval. The empirical results show that performances of our model are always better than the baseline obtained with the extended approach and also competitive with the standard approach

Has the digitalisation of the leisure air travel search industry been enabled by the characteristics of multi-sided platforms (MSPs)?

The air travel industry has been a front-runner in the development and adoption of new technologies in the past half century. The entry of metasearch companies into the leisure air travel search industry has changed the dynamic of consumer search completely. These metasearch companies operate a multi-sided platform in which they provide end users a free service where they can search, compare and analyse all of the flight options available them. This research studies whether the distinctive characteristics of multi-sided platforms (MSPs) have been the key enablers for the leisure air travel search industry to go through digitalisation. The main theoretical basis for this research was built from literature on platform technologies, with a focus on multi-sided platforms, and digitalisation. Based on past literature, a theoretical lens was developed, in order to identify the specific MSP characteristics that would used to analyse the upcoming data. A plan was created to conduct a qualitative study aimed at obtaining personal views and opinions on various themes regarding digitalisation in the leisure air travel search industry. The qualitative data was obtained utilizing both semi-structured interviews, as well as, written questionnaires, and the data received from the research was analysed in order to find similarities and themes regarding the research topics. The key themes that were formed from the qualitative study were all analysed regarding why they were viewed as important factors within the industry and how they had an effect on the way that the industry has gone through its digitalisation. The themes that emerged were technological milestones, seamless communication, customer loyalty programs, knowing your customers, and ownership of data. Each theme was also analysed in connection to the research question, in order to get overall conclusions for the study. Generally, the results from the study reflected well the existing literature on areas such as the benefits of using multi-sided platforms, the utilisation of customer loyalty programs, and the ability to successfully utilise customer data. In addition, the study provided great insight on the importance for a company to know ones customer and having the ability to recognize and adapt to changing customer demands. This study provides a good basis for further research on the topic, which could include a more extensive study from the consumer side, on what they value the most during the search phase of their leisure flights, and how they see the developments within the industry have changed their entire user experience