3763580
Extracting Features from Web Search Returned Hits for Hierarchical Classification
2743837
A hybrid classifier approach for Web retrieved documents classification
The paper presents a hybrid technique for the classification of Web returned hits into concept hierarchies. The technique involves a combination of manual and automatic classifiers. At first, all Web returned documents are assigned to human defined categories using manual classifiers, and then automatic classifiers are used to generate a concept hierarchy for each of these categories. The results of the evaluation reveal the following: (a) for polysemous queries, our system is able to generate meaningful categories corresponding to (but not limited to), the different semantic facets of the queries; (b) as expected, for non-polysemous queries the system generates fewer categories; (c) the hierarchy precision of the concept hierarchies generated for polysemous queries is found to be significantly better when compared to the one obtained using a baseline system.
62599943
Finding nuggets in documents: A machine learning approach
Document keyphrases provide a concise summary of a document's content, offering semantic metadata summarizing a document. They can be used in many applications related to knowledge management and text mining, such as automatic text summarization, development of search engines, document clustering, document classification, thesaurus construction, and browsing interfaces. Because only a small portion of documents have keyphrases assigned by authors, and it is time-consuming and costly to manually assign keyphrases to documents, it is necessary to develop an algorithm to automatically generate keyphrases for documents. This paper describes a Keyphrase Identification Program (KIP), which extracts document keyphrases by using prior positive samples of human identified phrases to assign weights to the candidate keyphrases. The logic of our algorithm is: The more keywords a candidate keyphrase contains and the more significant these keywords are, the more likely this candidate phrase is a keyphrase. KIP's learning function can enrich the glossary database by automatically adding new identified keyphrases to the database. KIP's personalization feature will let the user build a glossary database specifically suitable for the area of hissher interest. The evaluation results show that KIP's performance is better than the systems we compared to and that the learning function is effective. © 2006 Wiley Periodicals, Inc.
3822993
Learning by Examples: Identifying Key Concepts from Text Using Pre-Defined Inputs
16016667
Finding more useful information faster from web search results
In this paper, we propose a prototype system for automatic generation of concept hierarchies to be used as an overview of search results. The system sends a user's query to five search engines and receives a returned list of relevant web pages. The system then extracts query-oriented concept terms from snippets that come with the returned hits. Concept terms are organized into a concept hierarchy using a co-occurrence-based classification technique. Finally, concepts in returned documents are dynamically highlighted according to terms in the selected concept branch that lead to the chosen document. The user study shows that concept hierarchies do provide easy navigation and browsing of web returned documents. The results also show that users can find a document of interest no matter how low it is ranked in the retrieved list.
42417262
On the Minimum Common Integer Partition Problem
We introduce a new combinatorial optimization problem in this paper, called the Minimum Common Integer Partition (MCIP) problem, which was inspired by computational biology applications including ortholog assignment and DNA fingerprint assembly. A partition of a positive integer n is a multiset of positive integers that add up to exactly n, and an integer partition of a multiset S of integers is defined as the multiset union of partitions of integers in S. Given a sequence of multisets S1, ⋯, Sk of integers, where k ≥ 2, we say that a multiset is a common integer partition if it is an integer partition of every multiset Si, 1≤ i≤ k. The MCIP problem is thus defined as to find a common integer partition of S1, ⋯, Sk with the minimum cardinality. It is easy to see that the MCIP problem is NP-hard since it generalizes the well-known Set Partition problem. We can in fact show that it is APX-hard. We will also present a $\frac{5}{4}$-approximation algorithm for the MCIP problem when k = 2, and a $\frac{3k(k-1)}{3k-2}$-approximation algorithm for k ≥ 3.
14274462
Region-Based Image Clustering and Retrieval Using Multiple Instance Learning
Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. We propose an approach based on One-Class Support Vector Machine (SVM) to solve MIL problem in the region-based Content Based Image Retrieval (CBIR). This is an area where a huge number of image regions are involved. For the sake of efficiency, we adopt a Genetic Algorithm based clustering method to reduce the search space. Relevance Feedback technique is incorporated to provide progressive guidance to the learning process. Performance is evaluated and the effectiveness of our retrieval algorithm is demonstrated in comparative studies.
13960729
Multimodal user input patterns in a non-visual context
How will users choose between speech and hand inputs to perform tasks when they are given equivalent choices between both modalities in a non-visual interface? This exploratory study investigates this question. The study was conducted using AudioBrowser, a non-visual information access for the visually impaired. Findings include: (1) Users chose between input modalities based on the type of operations undertaken. Navigation operations primarily used hand input on the touchpad, while non-navigation instructions primarily used speech input. (2) Surprisingly, multimodal error correction was not prevalent. Repeating a failed operation until it succeeded and trying other methods in the same input modality were dominant error-correction strategies. (3) The modality learned first was not necessarily the primary modality used later, but a training order effect existed. These empirical results provide implications for designing non-visual multimodal input dialogues.
33892015
A Multiple-Criteria Quadratic Programming Approach to Network Intrusion Detection
The early and reliable detection and deterrence of malicious attacks, both from external and internal sources are a crucial issue for today’s e-business. There are various methods available today for intrusion detection; however, every method has its limitations and new approaches should still be explored. The objectives of this study are twofold: one is to discuss the formulation of Multiple Criteria Quadratic Programming (MCQP) approach, and to investigate the applicability of the quadratic classification method to the intrusion detection problem. The demonstration of successful Multiple Criteria Quadratic Programming application in intrusion detection can add another option to network security toolbox. The classification results are examined by cross-validation and improved by an ensemble method. The results demonstrated that MCQP is excellent and stable. Furthermore, the outcome of MCQP can be improved by the ensemble method.
35009889
Tree Domination in Graphs