Search results for "information retrieval"

Preface

2017

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…

Combining textual and visual cues for content-based image retrieval on the World Wide Web

2002

A system is proposed that combines textual and visual statistics in a single index vector for content-based search of a WWW image database. Textual statistics are captured in vector form using latent semantic indexing (LSI) based on text in the containing HTML document. Visual statistics are captured in vector form using color and orientation histograms. By using an integrated approach, it becomes possible to take advantage of possible statistical couplings between the content of the document (latent semantic content) and the contents of images (visual statistics). The combined approach allows improved performance in conducting content-based search. Search performance experiments are report…

Maximizing versus satisficing in the digital age: Disjoint scales and the case for “construct consensus”

2018

Abstract A question facing us today, in the new and rapidly evolving digital age, is whether searching for the best option – being a maximizer – leads to greater happiness and better outcomes than settling on the first good enough option found – or “satisficing.” Answers to this question inform behavioural insights to improve well-being and decision-making in policy and organizational settings. Yet, the answers to this fundamental question of measurement of the happiness of a maximizer versus a satisficer in the current psychological literature are: 1) conflicting; 2) anchored on the use of the first scale published to measure maximization as an individual-difference, and 3) unable to descr…

Causal inference in geosciences with kernel sensitivity maps

2020

Establishing causal relations between random variables from observational data is perhaps the most important challenge in today's Science. In remote sensing and geosciences this is of special relevance to better understand the Earth's system and the complex and elusive interactions between processes. In this paper we explore a framework to derive cause-effect relations from pairs of variables via regression and dependence estimation. We propose to focus on the sensitivity (curvature) of the dependence estimator to account for the asymmetry of the forward and inverse densities of approximation residuals. Results in a large collection of 28 geoscience causal inference problems demonstrate the…

Superposing significant interaction rules (SSIR) method: a simple procedure for rapid ranking of congeneric compounds

2020

The Superposing Significant Interaction Rules (SSIR) method is revised and implemented. The method is a simple combinatorial procedure, which deals with in situ generated rules among a dichotomized congeneric molecular family, selecting the most probabilistically relevant ones. The mere counting of the number of relevant rules attached to new compounds generates a molecular ranking useful for database filtering, refinement and prediction. The algorithm only needs for a symbolic molecular representation and this allows for mining the database in a confidential manner. Third parties will not know the real compounds that are on the way to be worked out. The procedure is tested for a complete s…

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…

Markov Model for Tweets Geographic Distribution Characterization

2015

Abstract In this paper we will continue our researches regarding e-Business and e-Government modeling on Social Media presented in (Stoica, Pitic, & Mihaescu, 2013). Among message and user parameters we add a new parameter used to describe the geographical dispersion of Twitter messages. This new parameter will characterize the way one set of messages will spread in Social Graph from the physical word point of view. The first model, presented as “A Novel Model for E-Business and E-Government Processes on Social”, will be extended with the geographical parameter PG. We will define and we will describe the Markov Model used to organize the messages gathered from social media. The main idea of…