16162932
AntSearch: An Ant Search Algorithm in Unstructured Peer-to-Peer Networks
The most prevalent peer-to-peer (P2P) application till today is file sharing, and unstructured P2P networks can support inherent heterogeneity of peers, are highly resilient to peers’ failures, and incur low overhead at peer arrivals and departures. Dynamic querying (DQ) is a new flooding technique which could estimate a proper time-to-live (TTL) value for a query flooding by estimating the popularity of the searched files, and retrieve sufficient results under controlled flooding range for reducing network traffic. Recent researches show that a large amount of peers in the P2P file sharing system are the free-riders, and queries are seldom hit by those peers. The free-riders problem causes a large amount of redundant messages in the DQ-like search algorithm. In this paper, we proposed a new search algorithm, called "AntSearch", to solve the problem. In AntSearch, each peer maintains its hit rate of previous queries, and records a list of pheromone values of its immediate neighbors. Based on the pheromone values, a query is only flooded to those peers which are not likely to be the free-riders. Our simulation results show that, compared with DQ and its enhanced algorithm DQ+, the AntSearch algorithm averagely reduces 50% network traffic at almost the same search latency as DQ+, while retrieving sufficient results for a query with a given required number of results.
6906500
Web Appearance Disambiguation of Personal Names Based on Network Motif
Searching for information about a particular person is a common activity on search engines. However, current search engines do not provide any special function for search a person. Previous research has solved the problem by using additional background knowledge, such as a friend list, to cluster the searched Web pages. However, it is still difficult to retrieve and choose suitable background knowledge. In this paper, we propose a Web appearance disambiguation (WAD) system to solve the problem by only using the hyperlink structures between Web pages. The key idea of the WAD system is to find out smaller node motifs as evidences of close relationship between pages for clustering searched Web pages. Our experimental results show that, under no background knowledge, the performance of the WAD system achieves 70% for the F-measure
6388420
Proof: A DHT-Based Peer-to-Peer Search Engine
In this paper we focus on building a large scale keyword search service over structured peer-to-peer (P2P) networks. Current state-of-the-art keyword search approaches for structured P2P systems are based on inverted list intersection. However, the biggest challenge in those approaches is that when the indices are distributed over peers, a simple query may cause a large amount of data to be transmitted over the network. We propose a new P2P keyword search scheme, called "Proof", to reduce network traffic for queries. The key idea is storing a content summary for each Web page in the inverted list, so that a query can be processed by only transmitting a small size of candidate results. Our simulation results showed that, compared with previous DHT-based P2P systems, Proof can dramatically reduce network traffic and computation time. It provides 100% precision and 90.09% recall of search results, at an acceptable cost of storage overhead, even when the number of peers and documents increases continually
29113389
Approximate string matching in LDAP based on edit distance
As the E-Commerce rapidly grows up, searching data is almost necessary in every application. Approximate string matching problems play a very important role to search with errors. Against these problems "Edit distance" and "Soundex" are two common techniques, especially the latter one is a "sound-like" method and had been applied to the LDAP server. Nevertheless, it is not adequate for certain situations especially when we perform the symbol matching (as in DNA); it doesn't make sense to use the "sound-like" method. On the other hand, "Edit distance" has a clear definition and also is widely used in many fields of application. Since the design of LDAP server is optimized for reading, applying edit distance technique to LDAP server has the problem of lowering speed. In this paper we design efficient data structures and an algorithm to solve the speed problem, and furthermore we use three filter conditions [1] based on the n-gram technique to achieve a well filter performance. Finally we also demonstrate experimentally the benefits of applying our algorithm and its limitations.
10296067
IRIS at TREC-8
We tested two relevance feedback models, an adaptive linear model and a probabilistic model, using massive feedback query expansion in TREC-5 (Sumner & Shaw, 1997), experimented with a three-valued scale of relevance and reduced feedback query expansion in TREC-6 (Sumner, Yang, Akers & Shaw, 1998), and examined the effectiveness of relevance feedback using a subcollection and the effect of system features in an interactive retrieval system called IRIS (Information Retrieval Interactive System) in TREC-7 (Yang, Maglaughlin, Mehol & Sumner, 1999). In TREC-8, we continued our exploration of relevance feedback approaches. Based on the result of our TREC-7 interactive experiment, which suggested relevance feedback using user-selected passages to be an effective alternative to conventional document feedback, our TREC-8 interactive experiment compared a passage feedback system and a document feedback system that were identical in all aspects except for the feedback mechanism. For the TREC-8 ad-hoc task, we merged results of pseudo-relevance feedback to subcollections as in TREC-7. Our results were consistent with that of TREC-7. The results of passage feedback, whose system log showed high level of searcher intervention, was superior to the document feedback results. As in TREC-7, our ad-hoc results showed high precision in top few documents, but performed poorly overall compared to results using the collection as a whole.
5335881
On statistical query sampling and NMR quantum computing
We introduce a "statistical query sampling" model, in which the goal of an algorithm is to produce an element in a hidden set S/spl sube/{0,1}/sup n/ with reasonable probability. The algorithm gains information about S through oracle calls (statistical queries), where the algorithm submits a query function g(/spl middot/) and receives an approximation to Pr/sub x/spl isin/S/[g(x)=1]. We show how this model is related to NMR quantum computing, in which only statistical properties of an ensemble of quantum systems can be measured, and in particular to the question of whether one can translate standard quantum algorithms to the NMR setting without putting all of their classical postprocessing into the quantum system. Using Fourier analysis techniques developed in the related context of statistical query learning, we prove a number of lower bounds (both information-theoretic and cryptographic) on the ability of algorithms to produce an x/spl isin/S, even when the set S is fairly simple. These lower bounds point out a difficulty in efficiently applying NMR quantum computing to algorithms such as Shor's and Simon's algorithm that involve significant classical postprocessing. We also explicitly relate the notion of statistical query sampling to that of statistical query learning.
37157806
An interactive WWW search engine for user-defined collections
Given the dynamic nature and the quantity of information on the WWW, many individual users and organizations compile and use focused WWW resource lists related to a particular topic or subject domain. The IRISWeb system extends this concept such that any user-defined set of WWW pages (a virtual collection) can be retrieved, indexed, and searched using a powerful full-text search engine with a relevance-feedback interface. This capability adds full-text searching to highly customized subsets of the WWW. Here we describe the IRISWeb software and an experiment that highlights its potential.
712798
IRIS at TREC-7
In our TREC-5 ad-hoc experiment, we tested two relevance feedback models, an adaptive linear model and a probabilistic model, using massive feedback query expansion (Sumner & Shaw, 1997). For our TREC-6 interactive experiment, we developed an interactive retrieval system called IRIS (Information Retrieval Interactive System), which implemented modified versions of the feedback models with a three-valued scale of relevance and reduced feedback query expansion (Sumner, Yang, Akers & Shaw, 1998). The goal of the IRIS design was to provide users with ample opportunities to interact with the system throughout the search process. For example, users could supplement the initial query by choosing from a list of statistically significant, two-word collocations, or add and delete query terms as well as change their weights at each search iteration. Unfortunately, it was difficult to tell how much effect each IRIS feature had on the retrieval outcome due to such factors as strong searcher effect and major differences between the experimental and control systems. In our TREC-7 interactive experiment, we attempted to isolate the effect of a given system feature by making the experimental and control systems identical, save for the feature we were studying. In one interactive experiment, the difference between the experimental and control systems was the display and modification capability of term weights. In another experiment, the difference was relevance feedback by passage versus document. For the TREC-7 ad-hoc task, we wanted to examine the effectiveness of relevance feedback using a subcollection in order to lay the groundwork for future participation in the Very Large Corpus experiment. Though the pre-test results showed the retrieval effectiveness of a subcollection approach to be competitive with a whole collection approach, we were not able to execute the subcollection retrieval in the actual ad-hoc experiment due to hardware problems. Instead, our ad-hoc experiment consisted of a simple initial retrieval run and a pseudo-relevance feedback run using the top 5 documents as relevant and the 100 document as non-relevant. Though the precision was high in the top few documents, the ad-hoc results were below average by TREC measures as expected. In the interactive experiment, the passage feedback results were better than the document feedback results, and the results of the simple interface system that did not display query term weights were better than that of the more complex interface system that displayed query term weights and allowed users to change these weights. Overall interactive results were about average among participants.
45289699
Strengthening Zero-Knowledge Protocols Using Signatures
Recently there has been an interest in zero-knowledge protocols with stronger properties, such as concurrency, unbounded simulation soundness, non-malleability, and universal composability. In this paper, we show a novel technique to convert a large class of existing honest-verifier zero-knowledge protocols into ones with these stronger properties in the common reference string model. More precisely, our technique utilizes a signature scheme existentially unforgeable against adaptive chosen-message attacks, and transforms any Σ-protocol (which is honest-verifier zero-knowledge) into an unbounded simulation sound concurrent zero-knowledge protocol. We also introduce Ω-protocols, a variant of Σ-protocols for which our technique further achieves the properties of non-malleability and/or universal composability. 
 
In addition to its conceptual simplicity, a main advantage of this new technique over previous ones is that it avoids the Cook-Levin theorem, which tends to be rather inefficient. Indeed, our technique allows for very efficient instantiation based on the security of some efficient signature schemes and standard number-theoretic assumptions. For instance, one instantiation of our technique yields a universally composable zero-knowledge protocol under the Strong RSA assumption, incurring an overhead of a small constant number of exponentiations, plus the generation of two signatures.