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.
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.
7799230
Passage feedback with IRIS
We compare a user-defined passage feedback (pf) system to a document feedback (df) system. Df employed the adaptive linear model for retrieval, while pf used weighted query expansion based on positive and negative feedback. Twenty-four searchers performed the same six tasks in varying search and system-order per TREC-8 guidelines. We hypothesized that pf, which featured interactive query expansion, would outperform df, which relied on automatic query expansion. Initial analysis appeared to reject this hypothesis, as df showed slightly higher overall performance than pf. However, analysis by system-order groups indicates only the first pf use had lower performance. These data suggest that pf was more difficult to learn than df, though the second pf use yielded competitive performance. If performance of pf is indeed affected by learning, an improved pf system with usability enhancements may prove to be an effective mechanism for interactive information retrieval.
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
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.
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
26832202
Approximate search engine optimization for directory service
Today, in many practical e-commerce systems, the real stored data usually are short strings, such as names, addresses, or other information. Searching data within these short strings is not the same as searching within longer strings. General search engines try their best to scan all long strings (or articles) quickly, and find out the places that match the search conditions. Some great online search algorithms (such as "agrep" as used inside glimpse, or "cgrep " as used inside compressed indices, or 'NR-grep') are proposed for searching without any indices in the sub-linear time O(n). However, for short strings (n is small), the practical performance of algorithms of O(n) and O(n) are much the same. Therefore, suitable indices are necessary to optimize the performance of the search engine. On the other hand, directory services are more and more important because of its optimization for searching data. The data stored in directory servers are almost short strings. The approximate search engine for directory service must take the properties of short strings into considerations. In our previous research, we have designed one approximate search engine especially for short strings by using filters to filter out the possible short strings, and then checking for the answers. However the performance of the previous search engine needs to be enhanced. In this paper, we propose new architecture and algorithm to optimize the performance of searching for directory service.
11653478
Design and empirical evaluation of search software for legal professionals on the WWW
Abstract Our research focuses on designing effective search aids for legal researchers interested in law-related information on the world wide web. In this paper we report on the design and evaluation of two software systems developed to explore models for browsing and searching across a user-selected set of WWW sites. A directory services tool, LIBClient, provides a hierarchical index of legal information resources in an interface emphasizing ease-of-use by Internet novices and management of multiple-site searching. To study the relative effectiveness of LIBClient in the hands of legal professionals, nineteen law students were observed using LIBClient and, in separate trials, the popular general-purpose search services to perform known-item searches within a fixed time limit. The experiment indicates the value of LIBClient for focused searching, most properly as a supplement to general-purpose search engines. Motivated by observations from the LIBClient study, a second retrieval experiment explores the effectiveness of a radically different LIBClient design in which the LIBClient interface is combined with a crawler-enhanced search engine, IRISWeb. The LIBClient–IRISWeb system enables full-text searching using natural language queries across a set of WWW pages collected by the IRISWeb crawler. The page harvesting process relies on a cascading set of filters to define the final set of WWW pages to be collected, including user selections in LIBClient, search results from site-specific search engines, and the hyperlink structure at target sites. To evaluate the LIBClient–IRISWeb method, the queries used in the user study are submitted to the system, with excellent retrieval results. In conclusion, our research points to the promise of WWW search tool designs that tightly couple directed browsing with query-based search capabilities using new forms of search automation.