Commit 6ba4aad4 authored by Victor Zimmermann's avatar Victor Zimmermann
Browse files

Spelling and lemmatisaton.

parent 87812127

src/absinth.py

+13 −13
Changes for src/absinth.py: 13 added lines, 13 removed lines.
Original line number Diff line number Diff line
@@ -168,7 +168,7 @@ def process_file(context_list, target_string, node_freq_dict, edge_freq_dict): 
                        

                        # Add only tokens with allowed tags to nodes.

                        elif token.tag_ in allowed_tag_list:

                            token_set.add(token.text)

                            token_set.add(token.lemma_)

                            

                    context_size = len(token_set)
@@ -209,20 +209,20 @@ def build_graph(node_freq_dict, edge_freq_dict): 
            tokens within every context the target occurs in.

    

    Returns:

        cooccurence_graph: Filtered undirected dice weighted small word 

            cooccurence graph for a given target entity.

        cooccurrence_graph: Filtered undirected dice weighted small word 

            cooccurrence graph for a given target entity.

    """

    

    min_node_freq = config.min_node_freq

    min_edge_freq = config.min_edge_freq

    max_weight = config.max_weight

    

    cooccurence_graph = nx.Graph()

    cooccurrence_graph = nx.Graph()

    

    for node, frequency in node_freq_dict.items():

        

        if frequency >= min_node_freq:

            cooccurence_graph.add_node(node)

            cooccurrence_graph.add_node(node)

            

    for node_tuple, frequency in edge_freq_dict.items():
@@ -230,11 +230,11 @@ def build_graph(node_freq_dict, edge_freq_dict): 
            

            continue

        

        elif node_tuple[0] not in cooccurence_graph.nodes:

        elif node_tuple[0] not in cooccurrence_graph.nodes:

            

            continue

        

        elif node_tuple[1] not in cooccurence_graph.nodes:

        elif node_tuple[1] not in cooccurrence_graph.nodes:

            

            continue
@@ -247,25 +247,25 @@ def build_graph(node_freq_dict, edge_freq_dict): 
            prob_0 = cooccurrence_frequency / node0_frequency

            prob_1 = cooccurrence_frequency / node1_frequency

            

            #best_weight = 1 - max(prob_0, prob_1)

            dice_weight = 1 - ((prob_0 + prob_1) / 2)

            best_weight = 1 - max(prob_0, prob_1)

            #dice_weight = 1 - ((prob_0 + prob_1) / 2)

            

            if dice_weight <= max_weight:

            if best_weight <= max_weight:

                

                cooccurence_graph.add_edge(*node_tuple, weight=dice_weight)

                cooccurrence_graph.add_edge(*node_tuple, weight=best_weight)

            

            else:

                

                pass

    

    return cooccurence_graph

    return cooccurrence_graph





def root_hubs(graph, edge_freq_dict):

    """Identifies senses (root hubs) by choosing nodes with high degrees

    

    Selects root hubs according to the algorithm in Véronis (2004). Nodes with

    high degree and neighbors with low weights (high cooccurence) are chosen

    high degree and neighbors with low weights (high cooccurrence) are chosen

    until there are no more viable candidates. A root hub candidate is every

    node that is not already a hub and is not a neighbor of one.