In this paper we describe the implementation of an extreme variation to the inverted file scheme. The scheme supports a comprehensive set of Boolean search operators, down to the single character level. When combined with a heuristic document ranking algorithm it supports retrieval of raw XML data, using the embedded tags as search arguments. We tested the system against a set of XML queries an...

The paper presents several techniques for selecting noun phrases for interactive query expansion following pseudo-relevance feedback and a new phrase search method. A combined syntactico-statistical method was used for the selection of phrases. First, noun phrases were selected using a part-ofspeech tagger and a noun-phrase chunker, and secondly, different statistical measures were applied to s...

This paper aims to provide high quality tags for digital images according to users’ interest. As there are three main elements in image tag recommendation problem, tensor factorization technology is utilized in this work. In this paper, the parameters of the tensor factorization model are represented as latent variables, and the key functions of the tensor factorization model can be implemented...

With the advent of Web 2.0 tagging became a popular feature in social media systems. People tag diverse kinds of content, e.g. products at Amazon, music at Last.fm, images at Flickr, etc. In the last years several researchers analyzed the impact of tags on information retrieval. Most works focussed on tags only and ignored context information. In this article we present context-aware approaches...

Web searching techniques have been investigated and implemented in many aspects. Particularly, in case of personalization, more important issue is how to manipulate the results retrieved from search engines for better user understandability and satisfaction. Such manipulation processes are i) ranking the results in accordance with user relevance, and ii) exchanging the results between users who...

We consider the problem of tag prediction in collaborative tagging systems where users share and annotate resources on theWeb.We put forward HAMLET, a novel approach to automatically propagate tags along the edges of a graph which relates similar documents. We identify the core principles underlying tag propagation for which we derive suitable scoring models combined in one overall ranking form...

In this paper we study the problem of automatic music tag annotation. Treating tag annotation as a computational classification process, we attempt to explore the relationship between acoustic features and music tags. Toward this end, we conduct a series of empirical experiments to evaluate a set of multi-label classifiers and demonstrate which ones are more suitable for music tag annotation. F...

Enterprise communication applications rely on automated reasoning about factors such as expertise for connecting people. Quantifying expertise is necessary for such applications because of the time constraints imposed by communications routing. This paper discusses the potential for collaborative tagging in the enterprise and how it enables the formation of social networks around tags or topics...

In this paper, we address the problem of landmark image annotation, defined as the task of automatically annotating a landmark query image with relevant descriptors (keywords or tags). Given a new query image along with its geolocation metadata (latitude and longitude), we retrieve several other images already available in a community image database (e.g., flickr.com, panoramio.com), found with...