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

Study of result presentation and interaction for aggregated search

The World Wide Web has always attracted researchers and commercial search engine companies due to the enormous amount of information available on it. "Searching" on web has become an integral part of today's world, and many people rely on it when looking for information. The amount and the diversity of information available on the Web has also increased dramatically. Due to which, the researchers and the search engine companies are making constant efforts in order to make this information accessible to the people effectively. Not only there is an increase in the amount and diversity of information available online, users are now often seeking information on broader topics. Users seeking information on broad topics, gather information from various information sources (e.g, image, video, news, blog, etc). For such information requests, not only web results but results from different document genre and multimedia contents are also becoming relevant. For instance, users' looking for information on "Glasgow" might be interested in web results about Glasgow, Map of Glasgow, Images of Glasgow, News of Glasgow, and so on. Aggregated search aims to provide access to this diverse information in a unified manner by aggregating results from different information sources on a single result page. Hence making information gathering process easier for broad topics. This thesis aims to explore the aggregated search from the users' perspective. The thesis first and foremost focuses on understanding and describing the phenomena related to the users' search process in the context of the aggregated search. The goal is to participate in building theories and in understanding constraints, as well as providing insights into the interface design space. In building this understanding, the thesis focuses on the click-behavior, information need, source relevance, dynamics of search intents. The understanding comes partly from conducting users studies and, from analyzing search engine log data. While the thematic (or topical) relevance of documents is important, this thesis argues that the "source type" (source-orientation) may also be an important dimension in the relevance space for investigating in aggregated search. Therefore, relevance is multi-dimensional (topical and source-orientated) within the context of aggregated search. Results from the study suggest that the effect of the source-orientation was a significant factor in an aggregated search scenario. Hence adds another dimension to the relevance space within the aggregated search scenario. The thesis further presents an effective method which combines rule base and machine learning techniques to identify source-orientation behind a user query. Furthermore, after analyzing log-data from a search engine company and conducting user study experiments, several design issues that may arise with respect to the aggregated search interface are identified. In order to address these issues, suitable design guidelines that can be beneficial from the interface perspective are also suggested. To conclude, aim of this thesis is to explore the emerging aggregated search from users' perspective, since it is a very important for front-end technologies. An additional goal is to provide empirical evidence for influence of aggregated search on users searching behavior, and identify some of the key challenges of aggregated search. During this work several aspects of aggregated search will be uncovered. Furthermore, this thesis will provide a foundations for future research in aggregated search and will highlight the potential research directions

Towards an Integrated Clickstream Data Analysis Framework for Understanding Web Users’ Information Behavior

Clickstream data offers an unobtrusive data source for understanding web users’ information behavior beyond searching. However, it remains underutilized due to the lack of structured analysis procedures. This paper provides an integrated framework for information scientists to employ in their exploitation of clickstream data, which could contribute to more comprehensive research on users’information behavior. Our proposed framework consists of two major components, i.e., data preparation and data investigation. Data preparation is the process of collecting, cleaning, parsing, and coding data, whereas data investigation includes examining data at three different granularity levels, namely, footprint, movement, and pathway. To clearly present our data analysis process with the analysis framework, we draw examples from an empirical analysis of clickstream data of OPAC users’ behavior. Overall, this integrated analysis framework is designed to be independent of any specific research settings so that it can be easily adopted by future researchers for their own clickstream datasets and research questions

Contexts and Contributions: Building the Distributed Library

This report updates and expands on A Survey of Digital Library Aggregation Services, originally commissioned by the DLF as an internal report in summer 2003, and released to the public later that year. It highlights major developments affecting the ecosystem of scholarly communications and digital libraries since the last survey and provides an analysis of OAI implementation demographics, based on a comparative review of repository registries and cross-archive search services. Secondly, it reviews the state-of-practice for a cohort of digital library aggregation services, grouping them in the context of the problem space to which they most closely adhere. Based in part on responses collected in fall 2005 from an online survey distributed to the original core services, the report investigates the purpose, function and challenges of next-generation aggregation services. On a case-by-case basis, the advances in each service are of interest in isolation from each other, but the report also attempts to situate these services in a larger context and to understand how they fit into a multi-dimensional and interdependent ecosystem supporting the worldwide community of scholars. Finally, the report summarizes the contributions of these services thus far and identifies obstacles requiring further attention to realize the goal of an open, distributed digital library system

iAggregator: Multidimensional Relevance Aggregation Based on a Fuzzy Operator

International audienceRecently, an increasing number of information retrieval studies have triggered a resurgence of interest in redefining the algorithmic estimation of relevance, which implies a shift from topical to multidimensional relevance assessment. A key underlying aspect that emerged when addressing this concept is the aggregation of the relevance assessments related to each of the considered dimensions. The most commonly adopted forms of aggregation are based on classical weighted means and linear combination schemes to address this issue. Although some initiatives were recently proposed, none was concerned with considering the inherent dependencies and interactions existing among the relevance criteria, as is the case in many real-life applications. In this article, we present a new fuzzy-based operator, called iAggregator, for multidimensional relevance aggregation. Its main originality, beyond its ability to model interactions between different relevance criteria, lies in its generalization of many classical aggregation functions. To validate our proposal, we apply our operator within a tweet search task. Experiments using a standard benchmark, namely, Text REtrieval Conference Microblog,1 emphasize the relevance of our contribution when compared with traditional aggregation schemes. In addition, it outperforms state-of-the-art aggregation operators such as the Scoring and the And prioritized operators as well as some representative learning-to-rank algorithms

Online Data Cleaning

Data-centric applications have never been more ubiquitous in our lives, e.g., search engines, route navigation and social media. This has brought along a new age where digital data is at the core of many decisions we make as individuals, e.g., looking for the most scenic route to plan a road trip, or as professionals, e.g., analysing customers’ transactions to predict the best time to restock different products. However, the surge in data generation has also led to creating massive amounts of dirty data, i.e., inaccurate or redundant data. Using dirty data to inform business decisions comes with dire consequences, for instance, an IBM report estimates that dirty data costs the U.S. $3.1 trillion a year. Dirty data is the product of many factors which include data entry errors and integration of several data sources. Data integration of multiple sources is especially prone to producing dirty data. For instance, while individual sources may not have redundant data, they often carry redundant data across each other. Furthermore, different data sources may obey different business rules (sometimes not even known) which makes it challenging to reconcile the integrated data. Even if the data is clean at the time of the integration, data updates would compromise its quality over time. There is a wide spectrum of errors that can be found in the data, e,g, duplicate records, missing values, obsolete data, etc. To address these problems, several data cleaning efforts have been proposed, e.g., record linkage to identify duplicate records, data fusion to fuse duplicate data items into a single representation and enforcing integrity constraints on the data. However, most existing efforts make two key assumptions: (1) Data cleaning is done in one shot; and (2) The data is available in its entirety. Those two assumptions do not hold in our age where data is highly volatile and integrated from several sources. This calls for a paradigm shift in approaching data cleaning: it has to be made iterative where data comes in chunks and not all at once. Consequently, cleaning the data should not be repeated from scratch whenever the data changes, but instead, should be done only for data items affected by the updates. Moreover, the repair should be computed effciently to support applications where cleaning is performed online (e.g. query time data cleaning). In this dissertation, we present several proposals to realize this paradigm for two major types of data errors: duplicates and integrity constraint violations. We frst present a framework that supports online record linkage and fusion over Web databases. Our system processes queries posted to Web databases. Query results are deduplicated, fused and then stored in a cache for future reference. The cache is updated iteratively with new query results. This effort makes it possible to perform record linkage and fusion effciently, but also effectively, i.e., the cache contains data items seen in previous queries which are jointly cleaned with incoming query results. To address integrity constraints violations, we propose a novel way to approach Functional Dependency repairs, develop a new class of repairs and then demonstrate it is superior to existing efforts, in runtime and accuracy. We then show how our framework can be easily tuned to work iteratively to support online applications. We implement a proof-ofconcept query answering system to demonstrate the iterative capability of our system

Untangling the Web: A Guide To Internet Research

[Excerpt] Untangling the Web for 2007 is the twelfth edition of a book that started as a small handout. After more than a decade of researching, reading about, using, and trying to understand the Internet, I have come to accept that it is indeed a Sisyphean task. Sometimes I feel that all I can do is to push the rock up to the top of that virtual hill, then stand back and watch as it rolls down again. The Internet—in all its glory of information and misinformation—is for all practical purposes limitless, which of course means we can never know it all, see it all, understand it all, or even imagine all it is and will be. The more we know about the Internet, the more acute is our awareness of what we do not know. The Internet emphasizes the depth of our ignorance because our knowledge can only be finite, while our ignorance must necessarily be infinite. My hope is that Untangling the Web will add to our knowledge of the Internet and the world while recognizing that the rock will always roll back down the hill at the end of the day

Semantically en enhanced information retrieval: an ontology-based aprroach

Tesis doctoral inédita. Universidad Autónoma de Madrid, Escuela Politécnica Superior, enero de 2009Bibliogr.: [227]-240 p