Abstract Several problems exist with traditional HMM based approaches for Web information extraction (IE) due to the lack of consideration on Web-specific features. To address this issue we present a Generalized Hidden Markov Model (GHMM) that extends HMMs by making use of Web-specific information for Web IE. In GHMM based approach, Web content blocks instead of terms are used as basic... Several problems exist with traditional HMM based approaches for Web information extraction (IE) due to the lack of consideration on Web-specific features. To address this issue we present a Generalized Hidden Markov Model (GHMM) that extends HMMs by making use of Web-specific information for Web IE. In GHMM based approach, Web content blocks instead of terms are used as basic extraction unit. Besides, instead of using the traditional sequential state transition order, GHMM decides the state transition order based on layout structure of the corresponding web page. Furthermore, GHMM uses multiple emission features derived from Web information instead of single emission feature. Experimental study shows that GHMM based approach can effectively improve Web IE comparing to traditional HMM based approaches. Read More Read Less

Abstract The explosive growth of online data and the diversity of goals that may be pursued over the web have significantly increased the monetary value of the web traffic. To tap into this accelerating market, web site operators try to increase their traffic by customizing their sites to the needs of specific users. Web site customization involves three great challenges: (i)... The explosive growth of online data and the diversity of goals that may be pursued over the web have significantly increased the monetary value of the web traffic. To tap into this accelerating market, web site operators try to increase their traffic by customizing their sites to the needs of specific users. Web site customization involves three great challenges: (i) the accurate identification of the user interests in the sites’ content (ii) the detection of the user goals in their site visits and (iii) the encapsulation of the user interests and goals into the sites’ presentation and content. In this paper, we study how we can effectively identify the user interests and goals in their site visits and we evaluate their correlation as this is exemplified in the users’ navigational patterns and the site’s semantic content and structure. Based on our findings we propose a novel recommendation mechanism that employs web mining techniques for suggesting customized site views that satisfy both the user preferences and goals. Our experimental evaluation shows that the user site interests and interaction goals can be accurately detected from the users’ navigational behavior and that our recommendation model, which uses the identified user preferences and goals yields significant improvements in the sites’ usability. Read More Read Less

Abstract Password based authentication schemes are commonly used to authenticate remote users. Many schemes have been proposed both with and without smart cards but each have its own merits and demerits. This paper analyzes the security of an enhanced Dynamic ID based remote user authentication scheme and shows that the enhanced scheme has major security weaknesses. The paper also presents a... Password based authentication schemes are commonly used to authenticate remote users. Many schemes have been proposed both with and without smart cards but each have its own merits and demerits. This paper analyzes the security of an enhanced Dynamic ID based remote user authentication scheme and shows that the enhanced scheme has major security weaknesses. The paper also presents a new scheme which overcomes the weaknesses and provides better security strength. Read More Read Less

Abstract We present in this paper the new concept of “actor databases” (DB-Act) being studied at the INI institute (Act21 project) where we are developing a parallel main memory database system based on an actor like data model. To achieve data distribution we use a Scalable Distributed Data Structures (SDDS) called “distributed Compact Trie Hashing” (CTH*) currently in development at the... We present in this paper the new concept of “actor databases” (DB-Act) being studied at the INI institute (Act21 project) where we are developing a parallel main memory database system based on an actor like data model. To achieve data distribution we use a Scalable Distributed Data Structures (SDDS) called “distributed Compact Trie Hashing” (CTH*) currently in development at the same project. Transaction management and recovery techniques are adapted for the combination of actors and SDDS in Act21. An adaptation of the nested transaction model to the actor paradigm is presented, as well as a recovery techniques using a fuzzy checkpointing tailored to the SDDS needs. Read More Read Less

Abstract Information retrieval is one of the major research areas due to accumulation of huge information in digital form. Various techniques of Information retrieval are based on the fact that terms contained in a document along with their frequency of occurrence signify the semantics of the document. Recent attempts to find the relevant document for a context represents documents in a... Information retrieval is one of the major research areas due to accumulation of huge information in digital form. Various techniques of Information retrieval are based on the fact that terms contained in a document along with their frequency of occurrence signify the semantics of the document. Recent attempts to find the relevant document for a context represents documents in a vector space model as document-term vector containing term weights for every index term in that document. As there will be enormous number of index terms this leads to high dimensionality problem. We can reduce the dimensionality based on the observation that groups of terms associated with related concepts occur together or do not occur in a document based on whether the document is relevant or not to that concept. Such a group of terms is identified as an equivalence class and can be viewed as a single dimension in a Rough set based information retrieval system. In this paper we present a hybrid clustering approach for the formation of equivalence classes of terms associated with related concepts. It uses the outcome of hierarchical clustering to provide seed points for implementing Incremental K-means algorithm. Due to the sparsity of the term vector the cosine similarity estimate was found to be ineffective for term clustering. Another promising measure of proximity estimate used in information retrieval namely Euclidian distance has a drawback that it is biased towards changes in the term frequencies in larger documents when the term weights are represented by tf-idf estimates. Hence we propose normalization for tf-idf estimates while representing a term as a vector in a document space before clustering the terms. Read More Read Less

Abstract In this paper we present JETCAT, a Japanese-English transfer-based machine translation system. Our main research contribution is that the transfer rules are not handcrafted but are learnt automatically from a parallel corpus. The system has been implemented in Amzi! Prolog, which offers scalability for large rule bases, full Unicode support for Japanese characters, and several APIs for the seamless integration... In this paper we present JETCAT, a Japanese-English transfer-based machine translation system. Our main research contribution is that the transfer rules are not handcrafted but are learnt automatically from a parallel corpus. The system has been implemented in Amzi! Prolog, which offers scalability for large rule bases, full Unicode support for Japanese characters, and several APIs for the seamless integration of the translation functionality into common office environments. As a first user interface we have developed a translation environment under Microsoft Word. The dynamic nature of our system allows for an easy customization of the rule base according to the user’s personal preferences by simply post-editing the translation results, which leads to an automatic update. The user interface for Microsoft Word also provides the possibility for the user to display token lists, parse trees, and transfer rules, which makes JETCAT also a very useful tool for language students. Read More Read Less