Search results for " information retrieval"
showing 10 items of 80 documents
An ontology-based retrieval system for mammographic reports
2015
In healthcare domain it can be useful to compare unstructured free-text clinical reports in order to enable the search for similar and/or relevant clinical cases. In data mining and text analysis tasks, the cosine similarity is usually used for texts comparison purposes. It is usually performed by computing the standard document vector cosine similarity between the two vectors representing the report pair under analysis. In this paper a novel system based on text pre-processing techniques and a modelled medical knowledge, using an improved radiological ontology, is proposed. Medical terms organized in a hierarchical tree can assess semantic similarity relationships between unstructured repo…
Collective Reasoning over Shared Concepts for the Linguistic Atlas of Sicily
2013
In this chapter, collective intelligence principles are applied in the context of the Linguistic Atlas of Sicily (ALS - Atlante Linguistico Siciliano), an interdisciplinary research focusing on the study of the Italian language as it is spoken in Sicily, and its correlation with the Sicilian dialect and other regional varieties spoken in Sicily. The project has been developed over the past two decades and includes a complex information system supporting linguistic research; recently it has grown to allow research scientists to cooperate in an integrated environment to produce significant scientific advances in the field of ethnologic and sociolinguistic research. An interoperable infrastruc…
Extracting Touristic Information from Online Image Collections
2012
In this paper, we present a Geographical Information Retrieval system, which aims to automatically extract and analyze touristic information from photos of online image collections (in our case of study Flickr). Our system collect all the photos, and the related information, that are associated to a specific city. We then use Google Maps service to geolocate the retrieved photos, and finally we analyze geo-referenced data to obtain our goals: 1) determining and locating the most interesting places of the city, i.e. the most visited locations, and 2) reconstructing touristic routes of the users visiting the city. Information is filtered by using a set of constraints, which we apply to select…
Visual Re-Ranking for Multi-Aspect Information Retrieval
2017
We present visual re-ranking, an interactive visualization technique for multi-aspect information retrieval. In multi-aspect search, the information need of the user consists of more than one aspect or query simultaneously. While visualization and interactive search user interface techniques for improving user interpretation of search results have been proposed, the current research lacks understanding on how useful these are for the user: whether they lead to quantifiable benefits in perceiving the result space and allow faster, and more precise retrieval. Our technique visualizes relevance and document density on a two-dimensional map with respect to the query phrases. Pointing to a locat…
AMUSED: An Annotation Framework of Multi-modal Social Media Data
2020
In this paper, we present a semi-automated framework called AMUSED for gathering multi-modal annotated data from the multiple social media platforms. The framework is designed to mitigate the issues of collecting and annotating social media data by cohesively combining machine and human in the data collection process. From a given list of the articles from professional news media or blog, AMUSED detects links to the social media posts from news articles and then downloads contents of the same post from the respective social media platform to gather details about that specific post. The framework is capable of fetching the annotated data from multiple platforms like Twitter, YouTube, Reddit.…
Identifying the k Best Targets for an Advertisement Campaign via Online Social Networks
2020
We propose a novel approach for the recommendation of possible customers (users) to advertisers (e.g., brands) based on two main aspects: (i) the comparison between On-line Social Network profiles, and (ii) neighborhood analysis on the On-line Social Network. Profile matching between users and brands is considered based on bag-of-words representation of textual contents coming from the social media, and measures such as the Term Frequency-Inverse Document Frequency are used in order to characterize the importance of words in the comparison. The approach has been implemented relying on Big Data Technologies, allowing this way the efficient analysis of very large Online Social Networks. Resul…
Clique Percolation Method: Memory Efficient Almost Exact Communities
2022
Automatic detection of relevant groups of nodes in large real-world graphs, i.e. community detection, has applications in many fields and has received a lot of attention in the last twenty years. The most popular method designed to find overlapping communities (where a node can belong to several communities) is perhaps the clique percolation method (CPM). This method formalizes the notion of community as a maximal union of $k$-cliques that can be reached from each other through a series of adjacent $k$-cliques, where two cliques are adjacent if and only if they overlap on $k-1$ nodes. Despite much effort CPM has not been scalable to large graphs for medium values of $k$. Recent work has sho…
Hybrid recommendation methods in complex networks
2015
We propose here two new recommendation methods, based on the appropriate normalization of already existing similarity measures, and on the convex combination of the recommendation scores derived from similarity between users and between objects. We validate the proposed measures on three relevant data sets, and we compare their performance with several recommendation systems recently proposed in the literature. We show that the proposed similarity measures allow to attain an improvement of performances of up to 20\% with respect to existing non-parametric methods, and that the accuracy of a recommendation can vary widely from one specific bipartite network to another, which suggests that a …
Environmental taxation, information precision, and information sharing
2022
We analyze how environmental taxes should be optimally levied when the regulators and firms face costs uncertainties in a Stackelberg-Cournot game. We allow linear-quadratic payoffs functions coupled with an affine information structure encompassing common and private information with noisy signals. In the first period, the regulator chooses the intensity of emissions taxes in order to reduce externalities. In the second period, facing industry-related and firm-specific shocks, firms compete in the marketplace as Cournot rivals and choose outputs. We show that, given costs uncertainties with non-uniform quality of signals across firms, the regulator sets differentiated tax policy. We also e…
Participation Costs and Inefficiency in Takeover Contests
2010
We consider a takeover in which risk neutral bidders incur private costs to participate to the auction. Supposing that valuations for target firm are common knowledge, we study the optimal strategy of bidders and analyze the takeover result when they get or not toeholds in the target firm. We found that bidder's decision of participation is endogenous. By analyzing bidder's condition of participation, we found that the probability that the potential bidder with the highest valuation will not participate to the control, exists. We show that this probability increases with the size of toeholds possessed by the bidder with low valuation. Nevertheless, the size of toeholds possessed by the bidd…