1,721,290 research outputs found
M. Faggioli & G. Turbanti, Il concilio inedito. Fonti del Vaticano II. 2001
No full textAubert Roger. M. Faggioli & G. Turbanti, Il concilio inedito. Fonti del Vaticano II. 2001. In: Revue théologique de Louvain, 33ᵉ année, fasc. 3, 2002. p. 447
M. Faggioli & G. Turbanti, Il concilio inedito. Fonti del Vaticano II. 2001
No full textAubert Roger. M. Faggioli & G. Turbanti, Il concilio inedito. Fonti del Vaticano II. 2001. In: Revue théologique de Louvain, 33ᵉ année, fasc. 3, 2002. p. 447
Comparing ANOVA Approaches to Detect Significantly Different IR Systems
No full textThe ultimate goal of the evaluation is to understand when two IR systems are (significantly) different. To this end, many comparison procedures have been developed over time. However, to date, most reproducibility efforts focused just on reproducing systems and algorithms, almost fully neglecting to investigate the reproducibility of the methods we use to compare our systems. In this paper, we focus on methods based on ANalysis Of VAriance (ANOVA), which explicitly model the data in terms of different contributing effects, allowing us to obtain a more accurate estimate of significant differences. In this context, we compare statistical analysis methods based on “traditional” ANOVA (tANOVA) to those based on a bootstrapped version of ANOVA (bANOVA) and those performing multiple comparisons relying on a more conservative Family-wise Error Rate (FWER) controlling approach to those relying on a more lenient False Discovery Rate (FDR) controlling approach. Our findings highlight that, compared to the tANOVA approaches, bANOVA presents greater statistical power, at the cost of lower stability
Evaluating Differential Privacy Approaches for Query Obfuscation in Information Retrieval
No full textProtecting the privacy of a user while they interact with an Information Retrieval (IR) system is crucial. This becomes more challenging when the IR system is not cooperative in satisfying the user’s privacy needs. Recent advancements in Natural Language Processing (NLP) have demonstrated Differential Privacy’s (DP) effectiveness in safeguarding text privacy for tasks like spam detection and sentiment analysis, even under the assumption of a non-cooperative system. Our investigation explores if DP methods, originally designed for specific NLP tasks, can effectively obscure queries in IR. Our analyses show that using the Vickrey DP mechanism, employing the Mahalanobis norm with a privacy budget ranging from ε = 10 to 12.5, provides cutting-edge privacy protection and enhances effectiveness. Unlike previous methods, DP allows users to fine-tune their desired level of privacy by adjusting the privacy budget ε. This flexibility offers a balance between how effective the system is and how much privacy is maintained, unlike the more rigid nature of previous approaches
Assessing the Semantic Difficulty of Queries
No full textTraditional Information Retrieval (IR) models, also known as lexical models, are hindered by the semantic gap, which refers to the mismatch between different representations of the same underlying concept. To address this gap, semantic models have been developed. Semantic and lexical models exploit complementary signals that are best suited for different types of queries. For this reason, these model categories should not be used interchangeably, but should rather be properly alternated depending on the query. Therefore, it is important to identify queries where the semantic gap is prominent and thus semantic models prove effective. In this work, we quantify the impact of using semantic or lexical models on different queries, and we show that the interaction between queries and model categories is large. Then, we propose a labeling strategy to classify queries into semantically hard or easy, and we deploy a prototype classifier to discriminate between them
What makes a query semantically hard?
Full text linkTraditional Information Retrieval (IR) models, also known as lexical models, are hindered by the semantic gap, which refers to the mismatch between different representations of the same underlying concept. To address this gap, semantic models have been developed. Semantic and lexical models exploit complementary signals that are best suited for different types of queries. For this reason, these model categories should not be used interchangeably, but should rather be properly alternated depending on the query. Therefore, it is important to identify queries where the semantic gap is prominent and thus semantic models prove effective. In this work, we quantify the impact of using semantic or lexical models on different queries, and we show that the interaction between queries and model categories is large. Then, we propose a labeling strategy to classify queries into semantically hard or easy, and we deploy a prototype classifier to discriminate between them
Query Obfuscation for Information Retrieval Through Differential Privacy
No full textProtecting the privacy of a user querying an Information Retrieval (IR) system is of utmost importance. The problem is exacerbated when the IR system is not cooperative in satisfying the user’s privacy requirements. To address this, obfuscation techniques split the user’s sensitive query into multiple non-sensitive ones that can be safely transmitted to the IR system. To generate such queries, current approaches rely on lexical databases, such as WordNet, or heuristics of word co-occurrences. At the same time, advances in Natural Language Processing (NLP) have shown the power of Differential Privacy (DP) in releasing privacy-preserving text for completely different purposes, such as spam detection and sentiment analysis. We investigate for the first time whether DP mechanisms, originally designed for specific NLP tasks, can effectively be used in IR to obfuscate queries. We also assess their performance compared to state-of-the-art techniques in IR. Our empirical evaluation shows that the Vickrey DP mechanism based on the Mahalanobis norm with privacy budget ε∈[10,12.5] achieves state-of-the-art privacy protection and improved effectiveness. Furthermore, differently from previous approaches that are substantially on/off, by changing the privacy budget ε, DP allows users to adjust their desired level of privacy protection, offering a trade-off between effectiveness and privacy
New Routes for Continuous Endovascular Advancement
No full textEndovenous techniques, such as pharmacomechanical
thrombolysis, catheter directed thrombolysis, and mechanical
thrombectomy are being employed increasingly to treat deep
vein diseases, such as thrombosis or post-thrombotic syndrome.
One of the key elements to achieving a high rate of
success is the choice of an appropriate venous access, to
provide a favourable approach the treatment site. In this
context, the popliteal vein is an appropriate site of venous
access for most treatments, given its anatomical position and
calibre. Usually, a percutaneous popliteal venous access is
obtained with the patient prone, under duplex ultrasound
guidance.
IR Systems Evaluation via Generalized Linear Models
Full text linkBeing able to compare Information Retrieval (IR) systems correctly is pivotal to improving their quality. Among the most popular tools for statistical significance testing, we list t-test and ANOVA that belong to the linear models family. Therefore, given the relevance of linear models for IR evaluation, a great effort has been devoted to studying how to improve them to better compare IR systems. Linear models rely on assumptions that IR experimental observations rarely meet, e.g. about the normality of the data or the linearity itself. Even though linear models are, in general, resilient to violations of their assumptions, departing from them might reduce the effectiveness of the tests. Hence, we investigate the use of the Generalized Linear Models (GLMs) framework, a generalization of the traditional linear modelling that relaxes assumptions about the distribution and the shape of the models. We discuss how GLMs can be applied in the context of IR evaluation. In particular, we focus on the link function used to build GLMs, which allows for the model to have non-linear shapes
Question Answering-Based Query Expansion for Conversational Search: IIIA@UNIPD at TREC CAsT 2022
No full text- …
