A conceptual heuristic for solving the maximum clique problem

The maximum clique problem (MCP) is the problem of finding the clique with maximum cardinality in a graph. It has been intensively studied for years by computer scientists and mathematicians. It has many practical applications and it is usually the computational bottleneck. Due to the complexity of the problem, exact solutions can be very computationally expensive. In the scope of this thesis, a polynomial time heuristic that is based on Formal Concept Analysis has been developed. The developed approach has three variations that use different algorithm design approaches to solve the problem, a greedy algorithm, a backtracking algorithm and a branch and bound algorithm. The parameters of the branch and bound algorithm are tuned in a training phase and the tuned parameters are tested on the BHOSLIB benchmark graphs. The developed approach is tested on all the instances of the DIMACS benchmark graphs, and the results show that the maximum clique is obtained for 70% of the graph instances. The developed approach is compared to several of the most effective recent algorithms.NPRP grant #06-1220-1-233 from the Qatar National Research Fund (a member of Qatar Foundation)

Technical Metrics Used to Evaluate Health Care Chatbots: Scoping Review

Dialog agents (chatbots) have a long history of application in health care, where they have been used for tasks such as supporting patient self-management and providing counseling. Their use is expected to grow with increasing demands on health systems and improving artificial intelligence (AI) capability. Approaches to the evaluation of health care chatbots, however, appear to be diverse and haphazard, resulting in a potential barrier to the advancement of the field. This study aims to identify the technical (nonclinical) metrics used by previous studies to evaluate health care chatbots. Studies were identified by searching 7 bibliographic databases (eg, MEDLINE and PsycINFO) in addition to conducting backward and forward reference list checking of the included studies and relevant reviews. The studies were independently selected by two reviewers who then extracted data from the included studies. Extracted data were synthesized narratively by grouping the identified metrics into categories based on the aspect of chatbots that the metrics evaluated. Of the 1498 citations retrieved, 65 studies were included in this review. Chatbots were evaluated using 27 technical metrics, which were related to chatbots as a whole (eg, usability, classifier performance, speed), response generation (eg, comprehensibility, realism, repetitiveness), response understanding (eg, chatbot understanding as assessed by users, word error rate, concept error rate), and esthetics (eg, appearance of the virtual agent, background color, and content). The technical metrics of health chatbot studies were diverse, with survey designs and global usability metrics dominating. The lack of standardization and paucity of objective measures make it difficult to compare the performance of health chatbots and could inhibit advancement of the field. We suggest that researchers more frequently include metrics computed from conversation logs. In addition, we recommend the development of a framework of technical metrics with recommendations for specific circumstances for their inclusion in chatbot studies

Ranking disagreement between graders: Application to ranking hadith scholars

Ranking raters based on their agreement or disagreement is a very active research field with many applications. It has been applied for instance for ranking automatic essay grading algorithms based on their agreement with human graders. Many metrics have been introduced for measuring agreement between graders with different performances depending on the type of data. In this paper, we apply the agreement measures on a new field which is the hadith authentication problem. Indeed, reported hadiths (actions or sayings of Prophet Muhamad PBUH) are not always authentic and scholars who study their authenticity often disagree on some hadiths. In this study, many metrics have been proposed and studied on a simulated data in order to determine which metric best reflects the measure of agreement especially in the presence of missing data. Best performing metric has been applied to real data in order to rank the hadith scholars. This study is a breakthrough in the science of hadith as it makes it possible to assign a confidence score to each authenticity judgment that reflects how often the hadith scholar in question agrees or disagrees with other scholars.Qatar National Research Fund, QNRF& Qatar Foundation, QFScopu

Prediction of date and ideology of old Islamic documents

Prediction of date and Ideology (aka Islamic school or Madhab) is a very important research field. It allows scholars and researchers to find out more about what is specific to a particular period of time and what the main topics of interest were during each period. It also makes it possible to see how each Islamic school differs from others. In this paper, we describe a new system for date and Islamic school prediction for one single page of text. Our method extracts the keywords using the hyper concept algorithm which outputs the keywords in a structured tree based on their importance. The keywords are then fed to a classification algorithm which predicts both the date and the Islamic school associated to each document. Experiments have been conducted on a large database crawled from Shamela online library. The results show that date prediction can be done with a root mean square error of about 200 years. Moreover, we study how the error varies with respect to the time period. This study is the first in its kind that gives a global overview of the Islamic jurisprudence heritage.Qatar National Research Fund, QNRF& Qatar Foundation, QFScopu

Authenticity detection as a binary text categorization problem: Application to Hadith authentication

Authentication of Hadiths (sayings of Prophet Muhammad) is very important field for religious scholars as well as historians. Authenticity verification is traditionally conducted by studying how trustworthy is each person in the narration chain. In this study, we propose a novel approach completely based on the content of each Hadith. For each category of hadiths (authentic and non-authentic), we create a binary relation in which the hadiths correspond to the objects of the relation and the words correspond to its attributes. Keywords for each category are then obtained in a hierarchical ordering of importance using the hyper rectangular decomposition. Classification is done by feeding the extracted keywords to a logistic regression classifier. The method has been validated on a database of about 1600 hadiths. Results show that classification accuracy increases with the number of annotators who agreed on the authenticity of each hadith. These findings suggest that our method successfully extracts relevant keywords and can be combined with other traditional methods. 2016 IEEE.Scopu

Inconsistency detection in Islamic advisory opinions using multilevel text categorization

Inconsistency detection is a large research area that has many applications. In the scope of Islamic content mining, this topic is of a particular interest because of the continuously increasing content and the need of people to find out more about its authenticity. Inconsistency detection is usually performed using linguistic analysis as well as the application of logic rules. We propose here a new method for inconsistency detection based on multilevel text categorization. For each categorization level, discriminative keywords are extracted using the hyper rectangular decomposition method which outputs the keywords in a hierarchical rank of importance. Then, those keywords are fed into the random forest classifier which automatically detects the category of each advisory opinion. Inconsistency detection is performed using an algorithm that detects inconsistent paths of advisory opinions. This study has been validated on a set of Islamic advisory opinions related to vows. The results are very interesting and show that our method is very promising in the field.This contribution was made possible by NPRP grant 06-1220-1-233 from the Qatar National Research Fund (a member of Qatar Foundation).Scopu