Above are papers related to the following paper: [Paper_ID] Paper #362926. 	[Title] A Common LISP Hypermedia Server [Abstract] A World-Wide Web (WWW) server was implemented in Common LISP in order to facilitate exploratory programming in the global hypermedia domain and to provide access to complex research programs, particularly artificial intelligence systems. The server was initially used to provide interfaces for document retrieval and for email servers. More advanced applications include interfaces to systems for inductive rule learning and natural-language question answering. Continuing research seeks to more fully generalize automatic form-processing techniques developed for email servers to operate seamlessly over the Web. The conclusions argue that presentation-based interfaces and more sophisticated form processing should be moved into the clients in order to reduce the load on servers and provide more advanced interaction models for users. Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #66596. 	[Title] Beyond Correlation: Bringing Artificial Intelligence to Events Data [Abstract] The Feature Vector Editor offers a user-extensible environment for exploratory data analysis. Several empirical studies have applied this environment to the SHER-FACS International Conflict Management dataset. Current analysis techniques include boolean analysis, temporal analysis, and automatic rule learning. Implemented portably in ANSI Common Lisp and the Common Lisp Interface Manager (CLIM), the system features an advanced interface that makes it intuitive for people to manipulate data and discover significant relationships. The system encapsulates data within objects and defines generic protocols that mediate all interactions between data, users and analysis algorithms. Generic data protocols make possible rapid integration of new datasets and new analytical algorithms with heterogeneous data formats. More sophisticated research reformulates SHERFACS conflict codings as machine-parsable narratives suitable for processing into semantic representations by the RELATUS Natural Language System. Experiments with 244 SHERFACS cases demonstrated the feasibility of building knowledge bases from synthetic texts exceeding 600 pages. Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #8821. 	[Title] Machine Learning Methods for International Conflict Databases: A Case Study in Predicting Mediation Outcome [Abstract] This paper tries to identify rules and factors that are predictive for the outcome of international conflict management attempts. We use C4.5, an advanced Machine Learning algorithm, for generating decision trees and prediction rules from cases in the CONFMAN database. The results show that simple patterns and rules are often not only more understandable, but also more reliable than complex rules. Simple decision trees are able to improve the chances of correctly predicting the outcome of a conflict management attempt. This suggests that mediation is more repetitive than conflicts per se, where such results have not been achieved so far. Please summarise all the given information.

Paper #362926 has the title `A Common LISP Hypermedia Server  
` and the abstract `A World-Wide Web (WWW) server was implemented in Common LISP in order to facilitate exploratory programming in the global hypermedia domain and to provide access to complex research programs, particularly artificial intelligence systems. The server was initially used to provide interfaces for document retrieval and for email servers. More advanced applications include interfaces to systems for inductive rule learning and natural-language question answering. Continuing research seeks to more fully generalize automatic form-processing techniques developed for email servers to operate seamlessly over the Web. The conclusions argue that presentation-based interfaces and more sophisticated form processing should be moved into the clients in order to reduce the load on servers and provide more advanced interaction models for users. 
`.
Question: Which category should Paper #362926 be classified as ?
You can select one from ['Neural_Networks', 'Case_Based', 'Theory', 'Reinforcement_Learning', 'Probabilistic_Methods', 'Rule_Learning', 'Genetic_Algorithms'].


Paper #362926 has the title `A Common LISP Hypermedia Server  
` and the abstract `A World-Wide Web (WWW) server was implemented in Common LISP in order to facilitate exploratory programming in the global hypermedia domain and to provide access to complex research programs, particularly artificial intelligence systems. The server was initially used to provide interfaces for document retrieval and for email servers. More advanced applications include interfaces to systems for inductive rule learning and natural-language question answering. Continuing research seeks to more fully generalize automatic form-processing techniques developed for email servers to operate seamlessly over the Web. The conclusions argue that presentation-based interfaces and more sophisticated form processing should be moved into the clients in order to reduce the load on servers and provide more advanced interaction models for users. 
`.
Question: Which category should Paper #362926 be classified as ?
You can select one from ['Neural_Networks', 'Case_Based', 'Theory', 'Reinforcement_Learning', 'Probabilistic_Methods', 'Rule_Learning', 'Genetic_Algorithms'].

This paper should be classified into: Rule_Learning