Yo-Sub Han

A movie recommendation algorithm based on genre correlations

Since the late 20th century, the number of Internet users has increased dramatically, as has the number of Web searches performed on a daily basis and the amount of information available. A huge amount of new information is transferred to the Web on a daily basis. However, not all data are reliable and valuable, which implies that it may become more and more difficult to obtain satisfactory results from Web searches. We often iterate searches several times to find what we are looking for. To solve this problem, researchers have suggested the use of recommendation systems. Instead of searching for the same information several times, a recommendation system proposes relevant information. In the Web 2.0 era, recommendation systems often rely on collaborative filtering by users. In general, a collaborative filtering approach based on user information such as gender, location, or preference is effective. However, the traditional approach can fail due to the cold-start problem or the sparsity problem, because initial user information is required for this approach to be effective. Recently, several attempts have been made to tackle these collaborative filtering problems. One such attempt used category correlations of contents. For instance, a movie has genre information provided by movie experts and directors. This category information is more reliable than user ratings. Moreover, newly created content always has category information, allowing avoidance of the cold-start problem. In this study, we consider a movie recommendation system and improve the previous algorithms based on genre correlations to correct its shortcomings. We also test the modified algorithm and analyze the results with respect to two characteristics of genre correlations.

Obtaining shorter regular expressions from finite-state automata

We consider the use of state elimination to construct shorter regular expressions from finite-state automata (FAs). Although state elimination is an intuitive method for computing regular expressions from FAs, the resulting regular expressions are often very long and complicated. We examine the minimization of FAs to obtain shorter expressions first. Then, we introduce vertical chopping based on bridge states and horizontal chopping based on the structural properties of given FAs. We prove that we should not eliminate bridge states until we eliminate all non-bridge states to obtain shorter regular expressions. In addition, we suggest heuristics for state elimination that leads to shorter regular expressions based on vertical chopping and horizontal chopping.

THE GENERALIZATION OF GENERALIZED AUTOMATA: EXPRESSION AUTOMATA

We explore expression automata with respect to determinism and minimization. We define determinism of expression automata using prefix-freeness. This approach is, to some extent, similar to that of...

Nondeterministic State Complexity of Basic Operations for Prefix-Free Regular Languages

We investigate the nondeterministic state complexity of basic operations for prefix-free regular languages. The nondeterministic state complexity of an operation is the number of states that are necessary and sufficient in the worst-case for a minimal nondeterministic finite-state automaton that accepts the language obtained from the operation. We establish the precise state complexity of catenation, union, intersection, Kleene star, reversal and complementation for prefix-free regular languages.

STATE COMPLEXITY OF UNION AND INTERSECTION OF FINITE LANGUAGES

We investigate the state complexity of union and intersection for finite languages. Note that the problem of obtaining the tight bounds for both operations was open. First we compute upper bounds using structural properties of minimal deterministic finite-state automata for finite languages. Then, we show that the upper bounds are tight if we have a variable sized alphabet that can depend on the size of input deterministic finite-state automata. In addition, we prove that the upper bounds are unreachable for any fixed sized alphabet.

INFIX-FREE REGULAR EXPRESSIONS AND LANGUAGES

We study infix-free regular languages. We observe the structural properties of finite-state automata for infix-free languages and develop a polynomial-time algorithm to determine infix-freeness of ...

Nondeterministic state complexity of nested word automata

We study the nondeterministic state complexity of Boolean operations on regular languages of nested words. For union and intersection we obtain matching upper and lower bounds. For complementation of a nondeterministic nested word automaton with n states we establish a lower bound @W(n!) that is significantly worse than the exponential lower bound for ordinary nondeterministic finite automata (NFA). We develop techniques to prove lower bounds for the size of nondeterministic nested word automata that extend the known techniques used for NFAs.

Representative reviewers for Internet social media

Our many various relationships with persons from home, work and school give rise to our social networks. In a social network, people receive, provide, and pass a great deal of information. In this process, we often observe that certain individuals have especially strong influences on others. We call these highly influential people opinion leaders. Since the late 20th century, the number of Internet users has increased rapidly, and a huge number of people now interact with each other in online social networks. In this way, the Web community has become similar to real-world society. Internet users receive information not only from the mass media, but also from opinion leaders. For example, online articles posted by influential bloggers are often used as marketing tools or political advertisements, due to their huge influence on other users. Therefore, it is important and useful to identify the influential users in an online society. We thus propose a simple yet reliable algorithm that identifies opinion leaders in a cyber social network. In this paper, we first describe our algorithm for identifying influential users in an online society. We then demonstrate the validity of the selection of representative reviewers using the Yahoo! music and GroupLens movie databases and performing 10-fold cross-validation and z-tests.

Evaluation of User Reputation on YouTube

In the Web 2.0 era, people not only read web contents but upload, view, share and evaluate all contents on the web. This leads us to introduce a new type of social network that is based on user activity and content metadata. Moreover, we can determine the quality of related contents using this new social network. Based on this observation, we introduce a user evaluation algorithm for user-generated video sharing website such as YouTube.

The generalization of generalized automata: expression automata

We explore expression automata with respect to determinism, minimization and primeness. We define determinism of expression automata using prefix-freeness. This approach is, to some extent, similar to that of Giammarresi and Montalbano’s definition of deterministic generalized automata. We prove that deterministic expression automata languages are a proper subfamily of the regular languages. We define the minimization of deterministic expression automata. Lastly, we discuss prime prefix-free regular languages. Note that we have omitted almost all proofs in this preliminary version.