Using micro information units for internet search
Internet search is one of the most important applications of the Web. A search engine takes the user's keywords to retrieve and to rank those pages that contain the keywords. One shortcoming of existing search techniques is that they do not give due consideration to the micro-structures of a Web page. A Web page is often populated with a number of small information units, which we call micro information units (MIU). Each unit focuses on a specific topic and occupies a specific area of the page. During the search, if all the keywords in the user query occur in a single MIU of a page, the top ranking results returned by a search engine are generally relevant and useful. However, if the query words scatter at different MIUs in a page, the pages returned can be quite irrelevant (which causes low precision). The reason for this is that although a page has information on individual MIUs, it may not have information on their intersections. In this paper, we propose a technique to solve this problem. At the off-line pre-processing stage, we segment each page to identify the MIUs in the page, and index the keywords of the page according to the MIUs in which they occur. In searching, our retrieval and ranking algorithm utilizes this additional information to return those most relevant pages. Experimental results show that this method is able to significantly improve the search precision.

title: Entity discovery and assignment for opinion mining applications
abstract: Opinion mining became an important topic of study in recent years due to its wide range of applications. There are also many companies offering opinion mining services. One problem that has not been studied so far is the assignment of entities that have been talked about in each sentence. Let us use forum discussions about products as an example to make the problem concrete. In a typical discussion post, the author may give opinions on multiple products and also compare them. The issue is how to detect what products have been talked about in each sentence. If the sentence contains the product names, they need to be identified. We call this problem entity discovery. If the product names are not explicitly mentioned in the sentence but are implied due to the use of pronouns and language conventions, we need to infer the products. We call this problem entity assignment. These problems are important because without knowing what products each sentence talks about the opinion mined from the sentence is of little use. In this paper, we study these problems and propose two effective methods to solve the problems. Entity discovery is based on pattern discovery and entity assignment is based on mining of comparative sentences. Experimental results using a large number of forum posts demonstrate the effectiveness of the technique. Our system has also been successfully tested in a commercial setting.

title: Dealing with different distributions in learning from
abstract: In the problem of learning with positive and unlabeled examples, existing research all assumes that positive examples P and the hidden positive examples in the unlabeled set U are generated from the same distribution. This assumption may be violated in practice. In such cases, existing methods perform poorly. This paper proposes a novel technique A-EM to deal with the problem. Experimental results with product page classification demonstrate the effectiveness of the proposed technique.

title: Finding Actionable Knowledge via Automated Comparison
abstract: The problem of finding interesting and actionable patterns is a major challenge in data mining. It has been studied by many data mining researchers. The issue is that data mining algorithms often generate too many patterns, which make it very hard for the user to find those truly useful ones. Over the years many techniques have been proposed. However, few have made it to real-life applications. At the end of 2005, we built a data mining system for Motorola (called Opportunity Map) to enable the user to explore the space of a large number of rules in order to find actionable knowledge. The approach is based on the concept of rule cubes and operations on rule cubes. A rule cube is similar to a data cube, but stores rules. Since its deployment, some issues have also been identified during the regular use of the system in Motorola. One of the key issues is that although the operations on rule cubes are flexible, each operation is primitive and has to be initiated by the user. Finding a piece of actionable knowledge typically involves many operations and intense visual inspections, which are labor-intensive and time-consuming. From interactions with our users, we identified a generic problem that is crucial for finding actionable knowledge. The problem involves extensive comparison of sub-populations and identification of the cause of their differences. This paper first defines the problem and then proposes an effective method to solve the problem automatically. To the best of our knowledge, there is no reported study of this problem. The new method has been added to the Opportunity Map system and is now in daily use in Motorola.

title: Opinion Mining
abstract: Описанл процедуру формування інтегрального показника об’єкта згідно з відгуками користувачів під час застосування методів оцінювання опінії текстової інформації у web-документах. Запропоновано використання лінгвістичних змінних та застосування вагових коефіцієнтів для достовірнішого результату оцінювання емоційного забарвлення текстової інформації. Ключові слова: опінія, емоційне забарвлення, об’єкт, інтегральний показник, лінгвістична змінна, ваговий коефіцієнт.

title: Speed-up iterative frequent itemset mining with constraint changes
abstract: Mining of frequent itemsets is a fundamental data mining task. Past research has proposed many efficient algorithms for this purpose. Recent work also highlighted the importance of using constraints to focus the mining process to mine only those relevant itemsets. In practice, data mining is often an interactive and iterative process. The user typically changes constraints and runs the mining algorithm many times before being satisfied with the final results. This interactive process is very time consuming. Existing mining algorithms are unable to take advantage of this iterative process to use previous mining results to speed up the current mining process. This results in an enormous waste of time and computation. In this paper, we propose an efficient technique to utilize previous mining results to improve the efficiency of current mining when constraints are changed. We first introduce the concept of tree boundary to summarize useful information available from previous mining. We then show that the tree boundary provides an effective and efficient framework for the new mining. The proposed technique has been implemented in the context of two existing frequent itemset mining algorithms, FP-tree and tree projection. Experiment results on both synthetic and real-life datasets show that the proposed approach achieves a dramatic saving of computation.

title: A Study on Information Extraction from PDF Files
abstract: Portable Document Format (PDF) is increasingly being recognized as a common format of electronic documents. The prerequisite to management and indexing of PDF files is to extract information from them. This paper describes an approach for extracting information from PDF files. The key idea is to transform the text information parsed from PDF files into semi-structured information by injecting additional uniform tags. An extensible rule set is built on tags and other knowledge. Guided by the rules, one pattern matching algorithm based on a tree model is applied to obtain the necessary information. A further experiment proved that this method was effective.

title: A Scalable Peer-to-Peer Overlay for Applications with Time Constraints
abstract: With the development of Internet, p2p is increasingly receiving attention in research. Recently, a class of p2p applications with time constraints appear. These applications require a short time to locate the resource and(or) a low transit delay between the resource user and the resource holder, such as Skype, MSN. In this paper we propose a scalable p2p overlay for applications with time constraints. Our system provides supports for just two operations for uplayered p2p applications: (1) Given a resource key and the node's IP who holds the resource, it registers the resource information to the associated node in at most two overlay hops; and (2) Given a resource key and a time constraint(0 for no constraint), it returns if possible a path(one or two overlay hops) to the resource holder, and the transit delay of the path is lower than the time constraint. Results from theoretical analysis and simulations show that our system is viable and scalable.

title: Accommodating colorblind users in image search
abstract: There are about 8% of men and 0.8% of women suffering from colorblindness. Due to certain loss of color information, the existing image search techniques may not provide satisfactory results for these users. In this demonstration, we show an image search system that can accommodate colorblind users. It can help these special users find and enjoy what they want by providing multiple services for them, including search results reranking, image recoloring and color indication.

title: A singular integral of the composite operator
abstract: We establish the Poincare-type inequalities for the composition of the homotopy operator and the projection operator. We also obtain some estimates for the integral of the composite operator with a singular density.

title: Reactive-ion etching of Ge2Sb2Te5 in CF4/Ar plasma for non-volatile phase-change memories
abstract: Etching of Ge"2Sb"2Te"5 (GST) is a critical step in the fabrication of chalcogenide random access memories. In this paper, the etch characteristics of GST films were studied with a CF"4/Ar gas mixture using a reactive-ion etching system. We observed a monotonic decrease in etch rate with decreasing CF"4 concentration indicating its importance in defining the material removal rate. Argon, on the other hand, plays an important role in defining the smoothness of the etched surface and sidewall edge acuity. We have studied the importance of gas mixture and RF power on the quality of the etched film. The smoothest surfaces and most vertical sidewalls were achieved using a CF"4/Ar gas mixture ratio of 10/40, a background pressure of 80mTorr, and power of 200W.