Carlo Gaibisso

Automatic construction of an opinion-term vocabulary for ad hoc retrieval

We present a method to automatically generate a term-opinion lexicon. We also weight these lexicon terms and use them at real time to boost the ranking with opinionated-content documents. We define very simple models both for opinion-term extraction and document ranking. Both the lexicon model and retrieval model are assessed. To evaluate the quality of the lexicon we compare performance with a well-established manually generated opinion-term dictionary. We evaluate the effectiveness of the term-opinion lexicon using the opinion task evaluation data of the TREC 2007 blog track.

The effect of cut-through switching on the performance of buffered banyan networks

Abstract This paper briefly reports on the results of some testing activities performed at IASI on the efficiency of multimedia conferencing on both local and wide-area packet switched networks. The aim of the testing was to study under which hypothesis it was possible to obtain acceptable - in terms of rate of information exchanged - multimedia conferencing sessions. A specific goal was to verify the possibility of obtaining an acceptable quality by using widely available, cheap resources. The tests performed have been carried out on an Ethernet LAN, connected to Internet by a 64Kbps link, using TCP/IP with multicast extension as transport protocol, in order to avoid IP datagrams multiplication when a multimedia conference involves more than two participants.Fast packet switches based on banyan interconnection networks and their variations are being proposed for Broadband Integrated Services Digital Network (B-1SDN). Previous analyses on buffered banyan networks mainly assume the store-and-forward operation of the switching systems. In this paper we study the effect of cut-through switching on buffered banyan networks. Two types of buffered banyan networks are considered: those with the switching elements employing input buffers and those employing output buffers. We extend the analytical method of Theimer et al. to multibuffered banyan networks, and to buffered banyan networks with output buffering in the switching elements. We present thc analyses of buffered banyan networks operating under cut-through switching. The results of these analyses confirm the simulation results, originally made by Bubenik and Turner. that cut-through switching in buffered banyan networks; improves both throughout and delay performances.

A CONVEX HULL ALGORITHM FOR POINTS WITH APPROXIMATELY KNOWN POSITIONS

We consider the problem of deriving good approximations of the convex hull of a set of points in the plane in the realistic case that only arbitrary finite approximations of the real valued coordinates can be known. In particular, the algorithm we introduce derives sequences of improved certified approximations converging to the exact solution, at the same time allowing the insertion of new points to the problem instance. The complexity analysis of the algorithm is performed by referring to a suitable computation model, based on a RAM with logarithmic costs, and the derived space and time bounds are shown to be competitive with respect to current off-line algorithms.

Survival analysis for freshness in microblogging search

Freshness of information in real-time search is central in social networks, news, blogs and micro-blogs. Nevertheless, there is not a clear experimental evidence that shows what principled approach effectively combines time and content. We introduce a novel approach to model freshness using a survival analysis of relevance over time. In such models, freshness is measured by the tail probability of relevance over time. We also assume that the probability distributions for freshness are heavy-tailed. The heavy-tailed models of freshness are shown to be highly effective on the micro-blogging test collection of TREC 2011. The improvements over the state-of-the-art time-based models are statistically significant or moderately significant.

On the design of efficient ATM routing schemes

In this paper we deal with the problem of designing virtual path layouts in ATM networks when the hop-count is given and the load has to be minimized. We first prove a lower bound for networks with arbitrary topology and arbitrary set of connection requests. This result is then applied to derive lower bounds for the following settings: (i) one-to-all (one node has to be connected to all other nodes of the network) in arbitrary networks; (ii) all-to-all (each node has to be connected to all other nodes in the network) in several classes of networks, including planar and k-separable networks and networks of bounded genus. We finally study the all-to-all setting on two-dimensional meshes and we design a virtual path layout for this problem. When the hop-count and the network degree are bounded by constants, our results show that the upper bounds proposed in this paper for the one-to-all problem in arbitrary networks and for the all-to-all problem in two-dimensional mesh networks are asymptotically optimal. Moreover, the general lower bound shows that the algorithm proposed in Gerstel (Ph.D. Thesis, Technion-Haifa, Israel, 1995) for the all-to-all problem in k-separable networks is also asymptotically optimal. The upper bound for mesh networks also shows that the lower bound presented in this paper for the all-to-all problem in planar networks is asymptotically tight.

On performance of topical opinion retrieval

We investigate the effectiveness of both the standard evaluation measures and the opinion component for topical opinion retrieval. We analyze how relevance is affected by opinions by perturbing relevance ranking by the outcomes of opinion-only classifiers built by Monte Carlo sampling. Topical opinion rankings are obtained by either re-ranking or filtering the documents of a first-pass retrieval of topic relevance. The proposed approach establishes the correlation between the accuracy and the precision of the classifier and the performance of the topical opinion retrieval. Among other results, it is possible to assess the effectiveness of the opinion component by comparing the effectiveness of the relevance baseline with the topical opinion ranking.

A Uniform Theoretic Approach to Opinion and Information Retrieval

In this paper, we introduce a supervised method for the generation of a dictionary of weighted opinion bearing terms from a collection of opinionated documents. We also describe how such a dictionary is used in the framework of an algorithm for opinion retrieval, that is for the problem of identifying the documents in a collection where some opinion is expressed with respect to a given query topic. Several experiments, performed on the TREC Blog collection, are reported together with their results; in these experiments, the use of different combinations of DFR (Divergence from Randomness) probabilistic models to assign weights to terms in the dictionary and to documents is studied and evaluated. The results show the stability of the method and its practical utility. Moreover, we investigate the composition of the generated lexicons, mainly focusing on the presence of stop-words. Quite surprisingly, the best performing dictionaries show a predominant presence of stop-words. Finally, we study the effectiveness of the same approach to generate dictionaries of polarity-bearing terms: preliminary results are provided.

Lower Bounds for the Virtual Path Layout Problem in ATM Networks

In this paper we deal with the problem of designing virtual path layouts in ATM networks with given hop-count and minimum load, for which we prove a lower bound with respect to networks with arbitrary topology. The result is then applied to derive a tight lower bound for the one-to-many communication pattern in networks with arbitrary topology, and for the many-to-many communication pattern in planar graphs and graphs with bounded treewidth.

Assessing the Quality of Opinion Retrieval Systems

Due to the complexity of topical opinion retrieval systems, standard measures, such as MAP or precision, do not fully succeed in assessing their performances. In this paper we introduce an evaluation framework based on artificially defined opinion classifiers. Using a Monte Carlo sampling, we perturb a relevance ranking by the outcomes of these classifiers and analyse how the opinion retrieval performance changes. In this way it is possible to assess the performance of an approach to opinion mining from that of the overall system and to clarify how relevance and opinion are affected by each other.

Transparent java threads migration protocol over peer2peer

The Java Virtual Machine computing model implements a multi-threading paradigm but its computing model does not define and does not verify the distribution paradigm of the threads over set of JVM instances. Without a distribution paradigm the Java Virtual Machine computing model cannot get any advantage from the theory of parallel Turing Machines. This work formally specifies and verifies the JVM computing model distribution paradigm. An intrinsic transparent thread distribution mechanism over many JVMs relying on different communication technology such as Peer to Peer is an important outcome of the presented solution. Other consequences, such as distributed JVM run-time location, aggregation and reachability, are achieved. Moreover the creation of Virtual Farms of JVMs for Multi-threading applications computing is made possible.