8799846
Syntactic features in question answering
Syntactic information potentially plays a much more important role in question answering than it does in information retrieval. Although many people have used syntactic evidence in Question Answering, there haven't been many detailed experiments reported in the literature. The aim of the experiment described in this paper is to study the impact of a particular approach for using syntactic information on question answering effectiveness. Our results indicate that a combination of syntactic information with heuristics for ranking potential answers can perform better than the ranking heuristics on their own.
13418116
An information-pattern-based approach to novelty detection
In this paper, a new novelty detection approach based on the identification of sentence level information patterns is proposed. First, ''novelty'' is redefined based on the proposed information patterns, and several different types of information patterns are given corresponding to different types of users' information needs. Second, a thorough analysis of sentence level information patterns is elaborated using data from the TREC novelty tracks, including sentence lengths, named entities (NEs), and sentence level opinion patterns. Finally, a unified information-pattern-based approach to novelty detection (ip-BAND) is presented for both specific NE topics and more general topics. Experiments on novelty detection on data from the TREC 2002, 2003 and 2004 novelty tracks show that the proposed approach significantly improves the performance of novelty detection in terms of precision at top ranks. Future research directions are suggested.
16393547
A new robust relevance model in the language model framework
In this paper, a new robust relevance model is proposed that can be applied to both pseudo and true relevance feedback in the language-modeling framework for document retrieval. There are at least three main differences between our new relevance model and other relevance models. The proposed model brings back the original query into the relevance model by treating it as a short, special document, in addition to a number of top-ranked documents returned from the first round retrieval for pseudo feedback, or a number of relevant documents for true relevance feedback. Second, instead of using a uniform prior as in the original relevance model proposed by Lavrenko and Croft, documents are assigned with different priors according to their lengths (in terms) and ranks in the first round retrieval. Third, the probability of a term in the relevance model is further adjusted by its probability in a background language model. In both pseudo and true relevance cases, we have compared the performance of our model to that of the two baselines: the original relevance model and a linear combination model. Our experimental results show that the proposed new model outperforms both of the two baselines in terms of mean average precision.
16221853
UMass at TREC 2004: Novelty and HARD
For the TREC 2004 Novelty track, UMass participated in all four tasks. Although finding relevant sentences was harder this year than last, we continue to show marked improvements over the baseline of calling all sentences relevant, with a variant of tfidf being the most successful approach. We achieve 5‐9% improvements over the baseline in locating novel sentences, primarily by looking at the similarity of a sentence to earlier sentences and focusing on named entities. For the High Accuracy Retrieval from Documents (HARD) track, we investigated the use of clarification forms, fixed- and variable-length passage retrieval, and the use of metadata. Clarification form results indicate that passage level feedback can provide improvements comparable to user supplied related-text for document evaluation and outperforms related-text for passage evaluation. Document retrieval methods without a query expansion component show the most gains from related-text. We also found that displaying the top passages for feedback outperformed displaying centroid passages. Named entity feedback resulted in mixed performance. Our primary findings for passage retrieval are that document retrieval methods performed better than passage retrieval methods on the passage evaluation metric of binary preference at 12,000 characters, and that clarification forms improved passage retrieval for every retrieval method explored. We found no benefit to using variable-length passages over fixed-length passages for this corpus. Our use of geography and genre metadata resulted in no significant changes in retrieval performance.
2304647
Evaluating Question-Answering Techniques in Chinese
An important first step in developing a cross-lingual question answering system is to understand whether techniques developed with English text will also work with other languages, such as Chinese. The Marsha Chinese question answering system described in this paper uses techniques similar to those used in the English systems developed for TREC. Marsha consists of three main components: the query processing module, the Hanquery search engine, and the answer extraction module. It also contains some specific techniques dealing with Chinese language characteristics, such as word segmentation and ordinals processing. Evaluation of the system is done using a method based on the TREC question-answering track. The results of the evaluation show that the performance of Marsha is comparable to some English question answering systems in TREC 8 track. An English language version of Marsha further indicates that the heuristics used are applicable to the English question answering task.
26669443
Bottom-up discovery of frequent rooted unordered subtrees
In the past decade, XML has emerged as the standard language for information exchanging over the Internet. Due to its tree-structure paradigm, XML is superior for its capability of storing, querying, and manipulating complex data. Therefore, discovering frequent tree patterns over tree-structured data has become an interesting topic for XML data management. In this paper, we propose a tree mining algorithm, named BUXMiner, for finding a special class of frequent trees, called rooted unordered trees, from a tree-structured database. BUXMiner employs an efficient bottom-up approach to enumerate all candidate trees over a compact global tree guide and computes the frequent trees based on the tree guide. In addition to BUXMiner, we also propose a mining approach called BUMXMiner to discover the maximal frequent rooted unordered trees. We compare BUXMiner with previous tree-structure mining algorithms, namely XQPMinerTID and FastXMiner, which were also proposed to discover rooted unordered trees. The experimental results show that our algorithm outperforms XQPMinerTID and FastXMiner in terms of efficiency. The performance results from real-world applications also indicate the usefulness of our proposed tree mining algorithms in a variety of web applications, such as analysis of web page access patterns and mining frequent XML query patterns for caching.
7335001
Pivotbrowser: a tag-space image searching prototype
We propose a novel iterative searching and refining prototype for tagged images. This prototype, named PivotBrowser, captures semantically similar tag sets in a structure called pivot. By constructing a pivot for a textual query, PivotBrowser first selects candidate images possibly relevant to the query. The tags contained in these candidate images are then selected in terms of their tag relevances to the pivot. The shortlisted tags are clustered and one of the tag clusters is used to select the results from the candidate images. Ranking of the images in each partition is based on their relevance to the tag cluster. With the guidance of the tag clusters presented, a user is able to perform searching and iterative query refinement.
11674907
An Analytic Model Predicting the Optimal Range for Maximizing 1-Hop Broadcast Coverage in Dense Wireless Networks
We present an analytic model to predict the optimal range for maximizing 1-hop broadcast coverage in dense ad-hoc wireless networks, using information like network density and node sending rate. We first derive a geometric-based, probabilistic model that describes the expected coverage as a function of range, sending rate and density. Because we can only solve the resulting equations numerically, we next develop extrapolations that find the optimum range for any rate and density given a single precomputed optimum. Finally using simulation, we show that in spite of many simplifications in the model, our extrapolation is able to predict the optimal range to within 16%.
29798457
Adaptive Image Segmentation Using Modified Pulse Coupled Neural Network
This paper proposes a novel image segmentation algorithm based on Pulse Coupled Neural Network (PCNN).Unlike the traditional PCNN image segmentation methods, the presented algorithm can achieve the optimum parameters automatically. Experimental results show its good performance and robustness. The research fruits have great importance both on the theory research and practical application of PCNN.
1979432
Using Fault Injection and Modeling to Evaluate the Performability of Cluster-Based Services
We propose a two-phase methodology for quantifying the performability (performance and availability) of cluster-based Internet services. In the first phase, evaluators use a fault-injection infrastructure to measure the impact of faults on the server's performance. In the second phase, evaluators use an analytical model to combine an expected fault load with measurements from the first phase to assess the server's performability. Using this model, evaluators can study the server's sensitivity to different design decisions, fault rates, and environmental factors. To demonstrate our methodology, we study the performability of 4 versions of the PRESS Web server against 5 classes of faults, quantifying the effects of different design decisions on performance and availability. Finally, to further show the utility of our model, we also quantify the impact of two hypothetical changes, reduced human operator response time and the use of RAIDs.