Query rewriting in information retrieval: automatic context extraction from local user documents to improve query results

The central objective of research in Information Retrieval (IR) is to discover new techniques to retrieve relevant information in order to satisfy an Information Need. The Information Need is satisfied when relevant information can be provided to the user. In IR, relevance is a fundamental concept which has changed over time, from popular to personal, i.e., what was considered relevant before was information for the whole population, but what is considered relevant now is specific information for each user. Hence, there is a need to connect the behavior of the system to the condition of a particular person and his social context; thereby an interdisciplinary sector called Human-Centered Computing was born. For the modern search engine, the information extracted for the individual user is crucial. According to the Personalized Search (PS), two different techniques are necessary to personalize a search: contextualization (interconnected conditions that occur in an activity), and individualization (characteristics that distinguish an individual). This movement of focus to the individual's need undermines the rigid linearity of the classical model overtaken the ``berry picking'' model which explains that the terms change thanks to the informational feedback received from the search activity introducing the concept of evolution of search terms. The development of Information Foraging theory, which observed the correlations between animal foraging and human information foraging, also contributed to this transformation through attempts to optimize the cost-benefit ratio. This thesis arose from the need to satisfy human individuality when searching for information, and it develops a synergistic collaboration between the frontiers of technological innovation and the recent advances in IR. The search method developed exploits what is relevant for the user by changing radically the way in which an Information Need is expressed, because now it is expressed through the generation of the query and its own context. As a matter of fact the method was born under the pretense to improve the quality of search by rewriting the query based on the contexts automatically generated from a local knowledge base. Furthermore, the idea of optimizing each IR system has led to develop it as a middleware of interaction between the user and the IR system. Thereby the system has just two possible actions: rewriting the query, and reordering the result. Equivalent actions to the approach was described from the PS that generally exploits information derived from analysis of user behavior, while the proposed approach exploits knowledge provided by the user. The thesis went further to generate a novel method for an assessment procedure, according to the "Cranfield paradigm", in order to evaluate this type of IR systems. The results achieved are interesting considering both the effectiveness achieved and the innovative approach undertaken together with the several applications inspired using a local knowledge base.

Pricing in stochastic-local volatility models with default

In recent years is becoming increasingly important to handle credit risk. Credit risk is the risk associated with the possibility of bankruptcy. More precisely, if a derivative provides for a payment at cert time T but before that time the counterparty defaults, at maturity the payment cannot be effectively performed, so the owner of the contract loses it entirely or a part of it. It means that the payoff of the derivative, and consequently its price, depends on the underlying of the basic derivative and on the risk of bankruptcy of the counterparty. To value and to hedge credit risk in a consistent way, one needs to develop a quantitative model. We have studied analytical approximation formulas and numerical methods such as Monte Carlo method in order to calculate the price of a bond. We have illustrated how to obtain fast and accurate pricing approximations by expanding the drift and diffusion as a Taylor series and we have compared the second and third order approximation of the Bond and Call price with an accurate Monte Carlo simulation. We have analysed JDCEV model with constant or stochastic interest rate. We have provided numerical examples that illustrate the effectiveness and versatility of our methods. We have used Wolfram Mathematica and Matlab.

Determination of local density of states in amorphous oxide semiconductors with Kelvin Probe Force Microscopy

Amorphous semiconductors are important materials as they can be deposited by physical deposition techniques on large areas and even on plastic substrates. Therefore, they are crucial for transistors in large active matrices for imaging and transparent wearable electronics. The most widely applied candidate for amorphous thin film transistors production is Indium Gallium Zinc Oxide (IGZO). It is attracting much interest because of its optical transparency, facile processing by sputtering deposition and notable improved charge carrier mobility with respect to hydrogenated amorphous silicon a-Si:H. Degradation of the device and long-term performance issues have been observed if IGZO thin film transistors are subjected to electrical stress, leading to a modification of IGZO channel properties and subthreshold slope. Therefore, it is of great interest to have a reliable and precise method to study the conduction band tail, and the density of states in amorphous semiconductors. The aim of this thesis is to develop a local technique using Kelvin Probe Force Microscopy to study the evolution of IGZO DOS properties. The work is divided into three main parts. First, solutions to the non-linear Poisson-Boltzmann equation of a metal-insulator-semiconductor junction describing the charge accumulation and its relation to DOS properties are elaborated. Second macroscopic techniques such as capacitance voltage (CV) measurements and photocurrent spectroscopy are applied to obtain a non-local estimate of band-tail DOS properties in thin film transistor samples. The third part of my my thesis is dedicated to the KPFM measurements. By fitting the data to the developed numerical model, important parameters describing the amorphous conduction band tail are obtained. The results are in excellent agreement with the macroscopic characterizations. KPFM result is comparable also with non-local optoelectronic characterizations, such as photocurrent spectroscopy.