In this article, a new unsupervised feature extraction method for aspect-based sentiment analysis... more In this article, a new unsupervised feature extraction method for aspect-based sentiment analysis is proposed. This method improves the performance of frequency based feature extraction by using an online search engine. Although frequency based feature extraction methods produce good precision and recall values on formal texts, they are not very successful on informal texts. Our proposed algorithm takes the features of items suggested by frequency based feature extraction methods, then, eliminates the features which do not co-occur with the item, whose features are sought, on the Web. Since the proposed method constructs the candidate feature set of the item from the Web, it is domain-independent. The results of experiments reveal that for informal Turkish texts, much higher performance than frequency based method is achieved.
The proliferation of social media has rendered it a critical arena for online marketing strategie... more The proliferation of social media has rendered it a critical arena for online marketing strategies. To optimize conversion rates, the landing pages must effectively respond to a visitor segment's pain points that they need solutions for. A one-size-fits-all approach is inadequate since even if the product meets the needs of all consumers, their priorities may diverge. In this study, we propose a pipeline for creating personalized landing pages that dynamically cater to visiting customers' specific concerns. As a use case, a pipeline will be utilized to create a personalized pharmacy discount card landing page, serving for the particular needs of chronic diabetics users seeking to purchase needed medications at a reduced cost. The proposed pipeline incorporates additional stages to augment the traditional online marketing funnel including acquisition of salient tweets, filtration of irrelevant ones, extraction of themes from relevant tweets, and generation of coherent paragraphs. To collect relevant tweets and reduce bias, Facebook groups and pages relevant to individuals with diabetes were leveraged. Pre-trained models such as BERT and RoBERTa were used to cluster the tweets based on their similarities. GuidedLDA exhibited superior performance in identifying customer priorities. Human evaluations revealed that personalized landing pages were more effective in getting the attention, building attraction by addressing their concerns and engaging the audiences. The proposed methodology offers a practical architecture for developing customized landing pages considering visiting customers' profiles and needs.
The web provides a suitable media for users to post comments on different topics. In most of such... more The web provides a suitable media for users to post comments on different topics. In most of such content, authors express different opinions on different features or aspects of the topic. In aspect based sentiment analysis, it is analyzed as to for which aspect which opinion is expressed. Once aspects are available, the next important step is to match aspects with correct sentiments. In this work, we investigate enhancements for two cases in matching step: extracting implicit aspects, and sentiment words whose polarity depends on the aspect. The techniques are applied on Turkish informal texts collected from a products forum. Experimental evaluation shows that additional steps applied for these cases improve the accuracy of aspect based sentiment analysis.
In hierarchal organizations, for assigning tasks to the divisions of the organization some constr... more In hierarchal organizations, for assigning tasks to the divisions of the organization some constraints must be satisfied. This article investigates one such problem in which there are k different tasks to be accomplished and each division’s performance on each task may be different and represented by a scalar value. In this article we formally introduce this real life decision problem, named as Maximum-Weighted Tree Matching Problem, and propose a genetic algorithm solution to it, and give some experimental results.
In hierarchical organizations, hierarchical structures naturally correspond to nested sets. That ... more In hierarchical organizations, hierarchical structures naturally correspond to nested sets. That is, we have a collection of sets such that for any two sets, either one of them is a subset of the other, or they are disjoint. In other words, a nested set system forms a hierarchy in the form of a tree structure. The task assignment problem on such hierarchical organizations is a real life problem. In this paper, we introduce the tree-like weighted set packing problem, which is a weighted set packing problem restricted to sets forming tree-like hierarchical structure. We propose a dynamic programming algorithm with cubic time complexity.
In this article, a new unsupervised feature extraction method for aspect-based sentiment analysis... more In this article, a new unsupervised feature extraction method for aspect-based sentiment analysis is proposed. This method improves the performance of frequency based feature extraction by using an online search engine. Although frequency based feature extraction methods produce good precision and recall values on formal texts, they are not very successful on informal texts. Our proposed algorithm takes the features of items suggested by frequency based feature extraction methods, then, eliminates the features which do not co-occur with the item, whose features are sought, on the Web. Since the proposed method constructs the candidate feature set of the item from the Web, it is domain-independent. The results of experiments reveal that for informal Turkish texts, much higher performance than frequency based method is achieved.
The proliferation of social media has rendered it a critical arena for online marketing strategie... more The proliferation of social media has rendered it a critical arena for online marketing strategies. To optimize conversion rates, the landing pages must effectively respond to a visitor segment's pain points that they need solutions for. A one-size-fits-all approach is inadequate since even if the product meets the needs of all consumers, their priorities may diverge. In this study, we propose a pipeline for creating personalized landing pages that dynamically cater to visiting customers' specific concerns. As a use case, a pipeline will be utilized to create a personalized pharmacy discount card landing page, serving for the particular needs of chronic diabetics users seeking to purchase needed medications at a reduced cost. The proposed pipeline incorporates additional stages to augment the traditional online marketing funnel including acquisition of salient tweets, filtration of irrelevant ones, extraction of themes from relevant tweets, and generation of coherent paragraphs. To collect relevant tweets and reduce bias, Facebook groups and pages relevant to individuals with diabetes were leveraged. Pre-trained models such as BERT and RoBERTa were used to cluster the tweets based on their similarities. GuidedLDA exhibited superior performance in identifying customer priorities. Human evaluations revealed that personalized landing pages were more effective in getting the attention, building attraction by addressing their concerns and engaging the audiences. The proposed methodology offers a practical architecture for developing customized landing pages considering visiting customers' profiles and needs.
The web provides a suitable media for users to post comments on different topics. In most of such... more The web provides a suitable media for users to post comments on different topics. In most of such content, authors express different opinions on different features or aspects of the topic. In aspect based sentiment analysis, it is analyzed as to for which aspect which opinion is expressed. Once aspects are available, the next important step is to match aspects with correct sentiments. In this work, we investigate enhancements for two cases in matching step: extracting implicit aspects, and sentiment words whose polarity depends on the aspect. The techniques are applied on Turkish informal texts collected from a products forum. Experimental evaluation shows that additional steps applied for these cases improve the accuracy of aspect based sentiment analysis.
In hierarchal organizations, for assigning tasks to the divisions of the organization some constr... more In hierarchal organizations, for assigning tasks to the divisions of the organization some constraints must be satisfied. This article investigates one such problem in which there are k different tasks to be accomplished and each division’s performance on each task may be different and represented by a scalar value. In this article we formally introduce this real life decision problem, named as Maximum-Weighted Tree Matching Problem, and propose a genetic algorithm solution to it, and give some experimental results.
In hierarchical organizations, hierarchical structures naturally correspond to nested sets. That ... more In hierarchical organizations, hierarchical structures naturally correspond to nested sets. That is, we have a collection of sets such that for any two sets, either one of them is a subset of the other, or they are disjoint. In other words, a nested set system forms a hierarchy in the form of a tree structure. The task assignment problem on such hierarchical organizations is a real life problem. In this paper, we introduce the tree-like weighted set packing problem, which is a weighted set packing problem restricted to sets forming tree-like hierarchical structure. We propose a dynamic programming algorithm with cubic time complexity.
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Papers by Ismail toroslu