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Personalization despite being an effective solution to the problem information overload remains tricky on account of multiple dimensions to consider. Furthermore, the challenge of avoiding overdoing personalization involves estimation of a…
Personalization is becoming very important direction in semantic web search for the users that needs to find appropriate information. In this paper, a classification of web personalization is proposed and semantic web search tools are…
The ever-growing number of venues publishing academic work makes it difficult for researchers to identify venues that publish data and research most in line with their scholarly interests. A solution is needed, therefore, whereby…
Online social media provide multiple ways to find interesting content. One important method is highlighting content recommended by user's friends. We examine this process on one such site, the news aggregator Digg. With a stochastic model…
It is now commonplace to observe that we are facing a deluge of online information. Researchers have of course long acknowledged the potential value of this information since digital traces make it possible to directly observe, describe and…
Modeling visual search not only offers an opportunity to predict the usability of an interface before actually testing it on real users, but also advances scientific understanding about human behavior. In this work, we first conduct a set…
Information retrieval in real-time search presents unique challenges distinct from those encountered in classical web search. These challenges are particularly pronounced due to the rapid change of user search intent, which is influenced by…
User implicit feedback plays an important role in recommender systems. However, finding implicit features is a tedious task. This paper aims to identify users' preferences through implicit behavioural signals for image recommendation based…
Accurately modeling user preferences is vital not only for improving recommendation performance but also for enhancing transparency in recommender systems. Conventional user profiling methods, such as averaging item embeddings, often…
Experience is what makes our life more effective that is why it is necessary to share experience among people. The use of information technologies is the most technological way to work with experience, and the use of the Web is the best way…
The widespread use of online review sites over the past decade has motivated businesses of all types to possess an expansive arsenal of user feedback to mark their reputation. Though a significant proportion of purchasing decisions are…
Product search serves as an important entry point for online shopping. In contrast to web search, the retrieved results in product search not only need to be relevant but also should satisfy customers' preferences in order to elicit…
Modern social platforms are characterized by the presence of rich user-behavior data associated with the publication, sharing and consumption of textual content. Users interact with content and with each other in a complex and dynamic…
In the view of massive content explosion in World Wide Web through diverse sources, it has become mandatory to have content filtering tools. The filtering of contents of the web pages holds greater significance in cases of access by…
With the World Wide Web's ubiquity increase and the rapid development of various online businesses, the complexity of web sites grow. The analysis of web user's navigational pattern within a web site can provide useful information for…
User-generated content is central to social computing scholarship. However, researchers and practitioners often presume that these users are alive. Failing to account for mortality is problematic in social media where an increasing number…
One of the main challenges in recommender systems is data sparsity which leads to high variance. Several attempts have been made to improve the bias-variance trade-off using auxiliary information. In particular, document modeling-based…
Users issue queries to Search Engines, and try to find the desired information in the results produced. They repeat this process if their information need is not met at the first place. It is crucial to identify the important words in a…
Retrieval and content management are assumed to be mutually exclusive. In this paper we suggest that they need not be so. In the usual information retrieval scenario, some information about queries leading to a website (due to `hits' or…
Content recommender systems are generally adept at maximizing immediate user satisfaction but to optimize for the \textit{long-run} user value, we need more statistically sophisticated solutions than off-the-shelf simple recommender…